Feedforward regulation ensures stability and rapid reversibility of a cellular state

Optogenetic control of pheromone gradients and mating behavior in budding yeast

During mating in budding yeast, cells use pheromones to locate each other and fuse. This model system has shaped our current understanding of signal transduction and cell polarization in response to extracellular signals. The cell populations producing extracellular signal landscapes themselves are, however, less well understood, yet crucial for functionally testing quantitative models of cell polarization and for controlling cell behavior through bioengineering approaches. Here we engineered optogenetic control of pheromone landscapes in mating populations of budding yeast, hijacking the mating-pheromone pathway to achieve spatial control of growth, cell morphology, cell-cell fusion, and distance-dependent gene expression in response to light. Using our tool, we were able to spatially control and shape pheromone gradients, allowing the use of a biophysical model to infer the properties of large-scale gradients generated by mating populations in a single, quantitative experimental setup, predicting that the shape of such gradients depends quantitatively on population parameters. Spatial optogenetic control of diffusible signals and their degradation provides a controllable signaling environment for engineering artificial communication and cell-fate systems in gel-embedded cell populations without the need for physical manipulation.

Dissecting reversible and irreversible single cell state transitions from gene regulatory networks

Understanding cell state transitions and their governing regulatory mechanisms remains one of the fundamental questions in biology. We develop a computational method, state transition inference using cross-cell correlations (STICCC), for predicting reversible and irreversible cell state transitions at single-cell resolution by using gene expression data and a set of gene regulatory interactions. The method is inspired by the fact that the gene expression time delays between regulators and targets can be exploited to infer past and future gene expression states. From applications to both simulated and experimental single-cell gene expression data, we show that STICCC-inferred vector fields capture basins of attraction and irreversible fluxes. By connecting regulatory information with systems' dynamical behaviors, STICCC reveals how network interactions influence reversible and irreversible state transitions. Compared to existing methods that infer pseudotime and RNA velocity, STICCC provides complementary insights into the gene regulation of cell state transitions.

Extracellular Signal-Regulated Kinases: One Pathway, Multiple Fates

This comprehensive review delves into the multifaceted aspects of ERK signaling and the intricate mechanisms underlying distinct cellular fates. ERK1 and ERK2 (ERK) govern proliferation, transformation, epithelial-mesenchymal transition, differentiation, senescence, or cell death, contingent upon activation strength, duration, and context. The biochemical mechanisms underlying these outcomes are inadequately understood, shaped by signaling feedback and the spatial localization of ERK activation. Generally, ERK activation aligns with the Goldilocks principle in cell fate determination. Inadequate or excessive ERK activity hinders cell proliferation, while balanced activation promotes both cell proliferation and survival. Unraveling the intricacies of how the degree of ERK activation dictates cell fate requires deciphering mechanisms encompassing protein stability, transcription factors downstream of ERK, and the chromatin landscape.

A Dynamic Control Center Based on a DNA Reaction Network for Programmable Building of DNA Nanostructures

DNA-based nanostructures allow for complex self-assembly with nanometer precision through the specificity of Watson-Crick base pairing, but network behavior-directed control of the kinetic process is less studied. Here we show how the DNA reaction network (DRN), which has emerged as a reliable and programmable way to implement artificial network dynamics, can be built as the control center of programmable nanostructures, allowing spatiotemporal control over the dynamic behavior of DNA nanotubes. We chose a common network motif in biological control systems, the feed-forward loop, as the model network and demonstrated that dynamic behaviors, such as self-tuning control and multilayer hierarchical assembly, could be programmed by constructing an inhibition network and an excitation network, separately, in buffer solution and inside protocells.

Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases

In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease.

Enzyme Trafficking and Co-Clustering Precede and Accurately Predict Human Breast Cancer Recurrences: An Interdisciplinary Review

Although great effort has been expended to understand cancer's origins, less attention has been given to the primary cause of cancer deaths - cancer recurrences and their sequelae. This interdisciplinary review addresses mechanistic features of aggressive cancer by studying metabolic enzyme patterns within ductal carcinoma in situ (DCIS) of the breast lesions. DCIS lesions from patients who did or did not experience a breast cancer recurrence were compared. Several proteins, including phospho-Ser226-glucose transporter type 1, phosphofructokinase type L and phosphofructokinase/fructose 2,6-bisphosphatase type 4 are found in nucleoli of ductal epithelial cells in samples from patients who will not subsequently recur, but traffic to the cell periphery in samples from patients who will experience a cancer recurrence. Large co-clusters of enzymes near plasmalemmata will enhance product formation because enzyme concentrations in clusters are very high while solvent molecules and solutes diffuse through small channels. These structural changes will accelerate aerobic glycolysis. Agglomerations of pentose phosphate pathway and glutathione synthesis enzymes enhance GSH formation. As aggressive cancer lesions are incomplete at early stages, they may be unrecognizable. We have found that machine learning provides superior analyses of tissue images and may be used to identify biomarker patterns associated with recurrent and non-recurrent patients with high accuracy. This suggests a new prognostic test to predict DCIS patients who are likely to recur and those who are at low risk for recurrence. Mechanistic interpretations provide a deeper understanding of anti-cancer drug action and suggest that aggressive metastatic cancer cells are sensitive to reductive chemotherapy.

Emergent Bistable Switches from the Incoherent Feed-Forward Signaling of a Positive Feedback Loop

Bistability is intrinsically connected to various decision making processes in living systems. The operating principles of a bistable switch, generated from a positive feedback loop, are well understood both in natural and synthetic settings. However, the fate of dynamic modularity of a positive feedback loop is unknown when it is connected to another dynamically modular signaling motif. In order to address this, here we investigate feed-forward signaling of a positive feedback loop to determine the fate of a bistable switch under such signaling. Using the potential energy based high-throughput bifurcation analysis method, we uncover that in addition to the conventional bistability the hybrid motifs generate various emergent bistable switches, namely mushroom and isola switches, which are not produced by the individual motifs. Using random parameter sampling, network perturbation, and phase plane analysis, we establish the design principles of such emergent behaviors. Incoherent feed-forward signaling of a positive feedback loop with distinct regulatory thresholds of the two arms of the feed-forward loop are the key requirements for such emergent behaviors. Our calculations show that the specific types of atypical bistable responses depend on the logic gate configuration of the signals. However, the emergent bistable behaviors of the hybrid networks do not depend on the nature of the positive feedback loop.

Rac-dependent feedforward autoactivation of NOX2 leads to oxidative burst

NADPH oxidase 2 (NOX2) produces the superoxide anion radical (O₂⁻), which has functions in both cell signaling and immune defense. NOX2 is a multimeric-protein complex consisting of several protein subunits including the GTPase Rac. NOX2 uniquely facilitates an oxidative burst, which is described by initially slow O₂⁻ production, which increases over time. The NOX2 oxidative burst is considered critical to immune defense because it enables expedited O₂⁻ production in response to infections. However, the mechanism of the initiation and progression of this oxidative burst and its implications for regulation of NOX2 have not been clarified. In this study, we show that the NOX2 oxidative burst is a result of autoactivation of NOX2 coupled with the redox function of Rac. NOX2 autoactivation begins when active Rac triggers NOX2 activation and the subsequent production of O₂⁻, which in turn activates redox-sensitive Rac. This activated Rac further activates NOX2, amplifying the feedforward cycle and resulting in a NOX2-mediated oxidative burst. Using mutagenesis-based kinetic and cell analyses, we show that enzymatic activation of Rac is exclusively responsible for production of the active Rac trigger that initiates NOX2 autoactivation, whereas redox-mediated Rac activation is the main driving force of NOX2 autoactivation and contributes to generation of ∼98% of the active NOX2 in cells. The results of this study provide insight into the regulation of NOX2 function, which could be used to develop therapeutics to control immune responses associated with dysregulated NOX2 oxidative bursts.

Mnemons and the memorization of past signaling events

Current advances are raising our awareness of the diverse roles that protein condensation plays in the biology of cells. Particularly, findings in organisms as diverse as yeast and Drosophila suggest that cells may utilize protein condensation to establish long-lasting changes in cellular activities and thereby encode a memory of past signaling events. Proteins that oligomerize to confer such cellular memory have been termed 'mnemons'. In the forming of super-assemblies, mnemons change their function and modulate the influence that the affected protein originally had on cellular processes. Because mnemon assemblies are self-templating, they allow cells to retain the memory of past decisions over larger timescales. Here, we review the mechanisms behind the formation of cellular memory with an emphasis on mnemon-mediated memorization of past signaling events.

The Path towards Predicting Evolution as Illustrated in Yeast Cell Polarity

A bottom-up route towards predicting evolution relies on a deep understanding of the complex network that proteins form inside cells. In a rapidly expanding panorama of experimental possibilities, the most difficult question is how to conceptually approach the disentangling of such complex networks. These can exhibit varying degrees of hierarchy and modularity, which obfuscate certain protein functions that may prove pivotal for adaptation. Using the well-established polarity network in budding yeast as a case study, we first organize current literature to highlight protein entrenchments inside polarity. Following three examples, we see how alternating between experimental novelties and subsequent emerging design strategies can construct a layered understanding, potent enough to reveal evolutionary targets. We show that if you want to understand a cell’s evolutionary capacity, such as possible future evolutionary paths, seemingly unimportant proteins need to be mapped and studied. Finally, we generalize this research structure to be applicable to other systems of interest.

Feed-forward regulatory loop driven by IRF4 and NF-κB in adult T-cell leukemia/lymphoma

Adult T-cell leukemia/lymphoma (ATL) is a highly aggressive hematological malignancy derived from mature CD4+ T-lymphocytes. Here, we demonstrate the transcriptional regulatory network driven by 2 oncogenic transcription factors, IRF4 and NF-κB, in ATL cells. Gene expression profiling of primary ATL samples demonstrated that the IRF4 gene was more highly expressed in ATL cells than in normal T cells. Chromatin immunoprecipitation sequencing analysis revealed that IRF4-bound regions were more frequently found in super-enhancers than in typical enhancers. NF-κB was found to co-occupy IRF4-bound regulatory elements and formed a coherent feed-forward loop to coordinately regulate genes involved in T-cell functions and development. Importantly, IRF4 and NF-κB regulated several cancer genes associated with super-enhancers in ATL cells, including MYC, CCR4, and BIRC3. Genetic inhibition of BIRC3 induced growth inhibition in ATL cells, implicating its role as a critical effector molecule downstream of the IRF4-NF-κB transcriptional network.

Integrating Old and New Paradigms of G1/S Control

The Cdk-Rb-E2F pathway integrates external and internal signals to control progression at the G1/S transition of the mammalian cell cycle. Alterations in this pathway are found in most human cancers, and specific cyclin-dependent kinase Cdk4/6 inhibitors are approved or in clinical trials for the treatment of diverse cancers. In the long-standing paradigm for G1/S control, Cdks inactivate the retinoblastoma tumor suppressor protein (Rb) through phosphorylation, which releases E2F transcription factors to drive cell-cycle progression from G1 to S. However, recent observations in the laboratory and clinic challenge central tenets of the current paradigm and demonstrate that our understanding of the Rb pathway and G1/S control is still incomplete. Here, we integrate these new findings with the previous paradigm to synthesize a current molecular and cellular view of the mammalian G1/S transition. A more complete and accurate understanding of G1/S control will lead to improved therapeutic strategies targeting the cell cycle in cancer.

A processive phosphorylation circuit with multiple kinase inputs and mutually diversional routes controls G1/S decision

Studies on multisite phosphorylation networks of cyclin-dependent kinase (CDK) targets have opened a new level of signaling complexity by revealing signal processing routes encoded into disordered proteins. A model target, the CDK inhibitor Sic1, contains linear phosphorylation motifs, docking sites, and phosphodegrons to empower an N-to-C terminally directed phosphorylation process. Here, we uncover a signal processing mechanism involving multi-step competition between mutually diversional phosphorylation routes within the S-CDK-Sic1 inhibitory complex. Intracomplex phosphorylation plays a direct role in controlling Sic1 degradation, and provides a mechanism to sequentially integrate both the G1- and S-CDK activities while keeping S-CDK inhibited towards other targets. The competing phosphorylation routes prevent premature Sic1 degradation and demonstrate how integration of MAPK from the pheromone pathway allows one to tune the competition of alternative phosphorylation paths. The mutually diversional phosphorylation circuits may be a general way for processing multiple kinase signals to coordinate cellular decisions in eukaryotes.

The decision of whether and when a cell divides is tightly controlled. Here, the authors show in yeast that there is a multi-step competition between different phosphorylation states and sites in the S phase CDK-Sic1 complex, which controls Sic1 degradation and coordinates the precise timing of the G1/S transition.

Constitutive expression of a fluorescent protein reports the size of live human cells

Cell size is important for cell physiology because it sets the geometric scale of organelles and biosynthesis. A number of methods exist to measure different aspects of cell size, but each has significant drawbacks. Here, we present an alternative method to measure the size of single human cells using a nuclear localized fluorescent protein expressed from a constitutive promoter. We validate this method by comparing it to several established cell size measurement strategies, including flow cytometry optical scatter, total protein dyes, and quantitative phase microscopy. We directly compare our fluorescent protein measurement with the commonly used measurement of nuclear volume and show that our measurements are more robust and less dependent on image segmentation. We apply our method to examine how cell size impacts the cell division cycle and reaffirm that there is a negative correlation between size at cell birth and G1 duration. Importantly, combining our size reporter with fluorescent labeling of a different protein in a different color channel allows measurement of concentration dynamics using simple wide-field fluorescence imaging. Thus, we expect our method will be of use to researchers interested in how dynamically changing protein concentrations control cell fates.

Role for androgens in determination of ovarian fate in the common snapping turtle, Chelydra serpentina

Sex steroids are involved in sex determination in almost all vertebrates, including species with temperature-dependent sex determination (TSD). It is well established that aromatase and estrogens are involved in ovary determination in TSD species. In contrast, the role of non-aromatizable androgens in TSD is less clear. In this study, we used dihydrotestosterone (DHT) and an antagonist of the mammalian androgen receptor (flutamide) to examine the impact of androgens on sex determination in the snapping turtle. We incubated eggs at a male-producing temperature and treated embryos with drug delivery vehicle (5 L ethanol), DHT in vehicle, or flutamide in vehicle during the sex-determining period. We then measured expression of markers for ovarian and testicular development and genes involved in steroidogenesis. A subset of embryos and hatchlings were collected for histological analysis of gonad differentiation and sex determination. DHT and flutamide both induced ovarian development: 100% of vehicle-treated hatchlings had testes, while 60% of DHT-treated and 32% flutamide-treated hatchlings had ovaries. DHT and flutamide treatments also had feminizing effects on gene expression patterns and the structure of embryonic gonads. DHT treatment increased expression of FoxL2, androgen receptor, aromatase and several steroidogenic genes. Flutamide produced a similar, but weaker, pattern of gene expression. Genes involved in testis development (Sox9 and Amh) were influenced by flutamide treatment. Our findings support the hypothesis that androgens and the androgen receptor are involved in ovary determination in the common snapping turtle.

A fully-automated, robust, and versatile algorithm for long-term budding yeast segmentation and tracking

Live cell time-lapse microscopy, a widely-used technique to study gene expression and protein dynamics in single cells, relies on segmentation and tracking of individual cells for data generation. The potential of the data that can be extracted from this technique is limited by the inability to accurately segment a large number of cells from such microscopy images and track them over long periods of time. Existing segmentation and tracking algorithms either require additional dyes or markers specific to segmentation or they are highly specific to one imaging condition and cell morphology and/or necessitate manual correction. Here we introduce a fully automated, fast and robust segmentation and tracking algorithm for budding yeast that overcomes these limitations. Full automatization is achieved through a novel automated seeding method, which first generates coarse seeds, then automatically fine-tunes cell boundaries using these seeds and automatically corrects segmentation mistakes. Our algorithm can accurately segment and track individual yeast cells without any specific dye or biomarker. Moreover, we show how existing channels devoted to a biological process of interest can be used to improve the segmentation. The algorithm is versatile in that it accurately segments not only cycling cells with smooth elliptical shapes, but also cells with arbitrary morphologies (e.g. sporulating and pheromone treated cells). In addition, the algorithm is independent of the specific imaging method (bright-field/phase) and objective used (40X/63X/100X). We validate our algorithm's performance on 9 cases each entailing a different imaging condition, objective magnification and/or cell morphology. Taken together, our algorithm presents a powerful segmentation and tracking tool that can be adapted to numerous budding yeast single-cell studies.

Modeling population dynamics in a microbial consortium under control of a synthetic pheromone-mediated communication system

Microbial consortia can be used to catalyze complex biotransformations. Tools to control the behavior of these consortia in a technical environment are currently lacking. In the present study, a synthetic biology approach was used to build a model consortium of two Saccharomyces cerevisiae strains where growth and expression of the fluorescent marker protein EGFP by the receiver strain is controlled by the concentration of α-factor pheromone, which is produced by the emitter strain. We have developed a quantitative experimental and theoretical framework to describe population dynamics in the model consortium. We measured biomass growth and metabolite production in controlled bioreactor experiments, and used flow cytometry to monitor changes of the subpopulations and protein expression under different cultivation conditions. This dataset was used to parameterize a segregated mathematical model, which took into account fundamental growth processes, pheromone-induced growth arrest and EGFP production, as well as pheromone desensitization after extended exposure. The model was able to predict the growth dynamics of single-strain cultures and the consortium quantitatively and provides a basis for using this approach in actual biotransformations.

Cdc48/p97 segregase is modulated by cyclin-dependent kinase to determine cyclin fate during G1 progression

Cells sense myriad signals during G1, and a rapid response to prevent cell cycle entry is of crucial importance for proper development and adaptation. Cln3, the most upstream G1 cyclin in budding yeast, is an extremely short-lived protein subject to ubiquitination and proteasomal degradation. On the other hand, nuclear accumulation of Cln3 depends on chaperones that are also important for its degradation. However, how these processes are intertwined to control G1-cyclin fate is not well understood. Here, we show that Cln3 undergoes a challenging ubiquitination step required for both degradation and full activation. Segregase Cdc48/p97 prevents degradation of ubiquitinated Cln3, and concurrently stimulates its ER release and nuclear accumulation to trigger Start. Cdc48/p97 phosphorylation at conserved Cdk-target sites is important for recruitment of specific cofactors and, in both yeast and mammalian cells, to attain proper G1-cyclin levels and activity. Cdk-dependent modulation of Cdc48 would subjugate G1 cyclins to fast and reversible state switching, thus arresting cells promptly in G1 at developmental or environmental checkpoints, but also resuming G1 progression immediately after proliferative signals reappear.

A Precise Cdk Activity Threshold Determines Passage through the Restriction Point

At the restriction point (R), mammalian cells irreversibly commit to divide. R has been viewed as a point in G1 that is passed when growth factor signaling initiates a positive feedback loop of Cdk activity. However, recent studies have cast doubt on this model by claiming R occurs prior to positive feedback activation in G1 or even before completion of the previous cell cycle. Here we reconcile these results and show that whereas many commonly used cell lines do not exhibit a G1 R, primary fibroblasts have a G1 R that is defined by a precise Cdk activity threshold and the activation of cell-cycle-dependent transcription. A simple threshold model, based solely on Cdk activity, predicted with more than 95% accuracy whether individual cells had passed R. That a single measurement accurately predicted cell fate shows that the state of complex regulatory networks can be assessed using a few critical protein activities.

Mitogen-activated protein kinase (MAPK) dynamics determine cell fate in the yeast mating response

In the yeast Saccharomyces cerevisiae, the exposure to mating pheromone activates a prototypic mitogen-activated protein kinase (MAPK) cascade and triggers a dose-dependent differentiation response. Whereas a high pheromone dose induces growth arrest and formation of a shmoo-like morphology in yeast cells, lower pheromone doses elicit elongated cell growth. Previous population-level analysis has revealed that the MAPK Fus3 plays an important role in mediating this differentiation switch. To further investigate how Fus3 controls the fate decision process at the single-cell level, we developed a specific translocation-based reporter for monitoring Fus3 activity in individual live cells. Using this reporter, we observed strikingly different dynamic patterns of Fus3 activation in single cells differentiated into distinct fates. Cells committed to growth arrest and shmoo formation exhibited sustained Fus3 activation. In contrast, most cells undergoing elongated growth showed either a delayed gradual increase or pulsatile dynamics of Fus3 activity. Furthermore, we found that chemically perturbing Fus3 dynamics with a specific inhibitor could effectively redirect the mating differentiation, confirming the causative role of Fus3 dynamics in driving cell fate decisions. MAPKs mediate proliferation and differentiation signals in mammals and are therapeutic targets in many cancers. Our results highlight the importance of MAPK dynamics in regulating single-cell responses and open up the possibility that MAPK signaling dynamics could be a pharmacological target in therapeutic interventions.

Fundamental trade-offs between information flow in single cells and cellular populations

Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

Spatial and temporal signal processing and decision making by MAPK pathways

Mitogen-activated protein kinase (MAPK) pathways are conserved from yeast to man and regulate a variety of cellular processes, including proliferation and differentiation. Recent developments show how MAPK pathways perform exquisite spatial and temporal signal processing and underscores the importance of studying the dynamics of signaling pathways to understand their physiological response. The importance of dynamic mechanisms that process input signals into graded downstream responses has been demonstrated in the pheromone-induced and osmotic stress-induced MAPK pathways in yeast and in the mammalian extracellular signal-regulated kinase MAPK pathway. Particularly, recent studies in the yeast pheromone response have shown how positive feedback generates switches, negative feedback enables gradient detection, and coherent feedforward regulation underlies cellular memory. More generally, a new wave of quantitative single-cell studies has begun to elucidate how signaling dynamics determine cell physiology and represents a paradigm shift from descriptive to predictive biology.

Dark-induced leaf senescence: new insights into a complex light-dependent regulatory pathway

563 I. 563 II. 564 III. 564 IV. 565 V. 565 VI. 567 VII. 567 568 References 568 SUMMARY: Leaf senescence - the coordinated, active process leading to the organized dismantling of cellular components to remobilize resources - is a fundamental aspect of plant life. Its tight regulation is essential for plant fitness and has crucial implications for the optimization of plant productivity and storage properties. Various investigations have shown light deprivation and light perception via phytochromes as key elements modulating senescence. However, the signalling pathways linking light deprivation and actual senescence processes have long remained obscure. Recent analyses have demonstrated that PHYTOCHROME-INTERACTING FACTORS (PIFs) are major transcription factors orchestrating dark-induced senescence (DIS) by targeting chloroplast maintenance, chlorophyll metabolism, hormone signalling and production, and the expression of senescence master regulators, uncovering potential molecular links to the energy deprivation signalling pathway. PIF-dependent feed-forward regulatory modules might be of critical importance for the highly complex and initially light-reversible DIS induction.

Cellular Advantages to Signaling in a Digital World

A newly revealed cellular strategy for modularizing function inspires engineers.

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.

Half dozen of one, six billion of the other: What can small- and large-scale molecular systems biology learn from one another?

Small-scale molecular systems biology, by which we mean the understanding of a how a few parts work together to control a particular biological process, is predicated on the assumption that cellular regulation is arranged in a circuit-like structure. Results from the omics revolution have upset this vision to varying degrees by revealing a high degree of interconnectivity, making it difficult to develop a simple, circuit-like understanding of regulatory processes. We here outline the limitations of the small-scale systems biology approach with examples from research into genetic algorithms, genetics, transcriptional network analysis, and genomics. We also discuss the difficulties associated with deriving true understanding from the analysis of large data sets and propose that the development of new, intelligent, computational tools may point to a way forward. Throughout, we intentionally oversimplify and talk about things in which we have little expertise, and it is likely that many of our arguments are wrong on one level or another. We do believe, however, that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach, and our goal is to provoke thought along these lines.

Network motif-based method for identifying coronary artery disease

The present study aimed to develop a more efficient method for identifying coronary artery disease (CAD) than the conventional method using individual differentially expressed genes (DEGs). GSE42148 gene microarray data were downloaded, preprocessed and screened for DEGs. Additionally, based on transcriptional regulation data obtained from ENCODE database and protein-protein interaction data from the HPRD, the common genes were downloaded and compared with genes annotated from gene microarrays to screen additional common genes in order to construct an integrated regulation network. FANMOD was then used to detect significant three-gene network motifs. Subsequently, GlobalAncova was used to screen differential three-gene network motifs between the CAD group and the normal control data from GSE42148. Genes involved in the differential network motifs were then subjected to functional annotation and pathway enrichment analysis. Finally, clustering analysis of the CAD and control samples was performed based on individual DEGs and the top 20 network motifs identified. In total, 9,008 significant three-node network motifs were detected from the integrated regulation network; these were categorized into 22 interaction modes, each containing a minimum of one transcription factor. Subsequently, 1,132 differential network motifs involving 697 genes were screened between the CAD and control group. The 697 genes were enriched in 154 gene ontology terms, including 119 biological processes, and 14 KEGG pathways. Identifying patients with CAD based on the top 20 network motifs provided increased accuracy compared with the conventional method based on individual DEGs. The results of the present study indicate that the network motif-based method is more efficient and accurate for identifying CAD patients than the conventional method based on individual DEGs.

Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi

Although cell cycle control is an ancient, conserved, and essential process, some core animal and fungal cell cycle regulators share no more sequence identity than non-homologous proteins. Here, we show that evolution along the fungal lineage was punctuated by the early acquisition and entrainment of the SBF transcription factor through horizontal gene transfer. Cell cycle evolution in the fungal ancestor then proceeded through a hybrid network containing both SBF and its ancestral animal counterpart E2F, which is still maintained in many basal fungi. We hypothesize that a virally-derived SBF may have initially hijacked cell cycle control by activating transcription via the cis-regulatory elements targeted by the ancestral cell cycle regulator E2F, much like extant viral oncogenes. Consistent with this hypothesis, we show that SBF can regulate promoters with E2F binding sites in budding yeast.

DOI:http://dx.doi.org/10.7554/eLife.09492.001

Living cells grow and divide with remarkable precision to ensure that their genetic material is faithfully duplicated and distributed equally to the newly formed daughter cells. This precision is achieved through a series of steps known as the cell cycle. The cell cycle is ancient and conserved across all Eukaryotes, including plants, animals and fungi. However, some of the core proteins present in animals and fungi are unrelated. This raises the question as to how a drastic change could have occurred and been tolerated over evolution.

In animals and plants, a protein called E2F controls the expression of genes that are needed to begin the cell cycle. In most fungi, an equivalent protein called SBF performs the same role as E2F, but the two proteins are very different and do not appear to share a common ancestor. This is unexpected given that fungi and animals are more closely related to one another than either is to plants.

Medina et al. searched the genomes of many animals, fungi, plants, algae, and their closest relatives for genes that encoded proteins like E2F and SBF. SBF-like proteins were only found in fungi, yet some fungal groups had cell cycle regulators like those found in animals. Zoosporic fungi, which diverged early from the fungal ancestor, had both SBF- and E2F-like proteins, while many fungi later lost E2F during evolution.

So how did fungi acquire SBF? Medina et al. observed that part of the SBF protein is similar to proteins found in many viruses. The broad distribution of these viral SBF-like proteins suggests that they arose first in viruses, and a fungal ancestor acquired one such protein during a viral infection. As SBF and E2F bind similar DNA sequences, Medina et al. hypothesized that this viral SBF hijacked control of the cell cycle in the fungal ancestor by controlling expression of genes that were originally controlled only by E2F. In support of this idea, experiments showed that many E2F binding sites in modern genes are also SBF binding sites, and that E2F sites can substitute for SBF sites in SBF-controlled genes. Future experiments in zoosporic fungi, which have animal-like and fungal-like features, would provide a glimpse of how a fungal ancestor may have used both SBF and E2F. These experiments may also reveal why most fungi have retained the newer SBF but lost the ancestral and widely conserved E2F protein.

DOI:http://dx.doi.org/10.7554/eLife.09492.002

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.

Docking interactions: cell-cycle regulation and beyond

In budding yeast, the mating pathway activates Far1 to inhibit G1 cyclins in complex with the cyclin-dependent kinase (Cln-Cdk). Yet, the molecular mechanism has remained largely unclear for over 20 years. A recent report helps shed light on this regulation.

A TORC2-Akt Feed-Forward Topology Underlies HER3 Resiliency in HER2-Amplified Cancers

The requisite role of HER3 in HER2-amplified cancers is beyond what would be expected as a dimerization partner or effector substrate and it exhibits a substantial degree of resiliency that mitigates the effects of HER2-inhibitor therapies. To better understand the roots of this resiliency, we conducted an in-depth chemical-genetic interrogation of the signaling network downstream of HER3. A unique attribute of these tumors is the deregulation of TORC2. The upstream signals that ordinarily maintain TORC2 signaling are lost in these tumors, and instead TORC2 is driven by Akt. We find that in these cancers HER3 functions as a buffering arm of an Akt-TORC2 feed-forward loop that functions as a self-perpetuating module. This network topology alters the role of HER3 from a conditionally engaged ligand-driven upstream physiologic signaling input to an essential component of a concentric signaling throughput highly competent at preservation of homeostasis. The competence of this signaling topology is evident in its response to perturbation at any of its nodes. Thus, a critical pathophysiologic event in the evolution of HER2-amplified cancers is the loss of the input signals that normally drive TORC2 signaling, repositioning it under Akt dependency, and fundamentally altering the role of HER3. This reprogramming of the downstream network topology is a key aspect in the pathogenesis of HER2-amplified cancers and constitutes a formidable barrier in the targeted therapy of these cancers.

A Cellular System for Spatial Signal Decoding in Chemical Gradients

Directional cell growth requires that cells read and interpret shallow chemical gradients, but how the gradient directional information is identified remains elusive. We use single-cell analysis and mathematical modeling to define the cellular gradient decoding network in yeast. Our results demonstrate that the spatial information of the gradient signal is read locally within the polarity site complex using double-positive feedback between the GTPase Cdc42 and trafficking of the receptor Ste2. Spatial decoding critically depends on low Cdc42 activity, which is maintained by the MAPK Fus3 through sequestration of the Cdc42 activator Cdc24. Deregulated Cdc42 or Ste2 trafficking prevents gradient decoding and leads to mis-oriented growth. Our work discovers how a conserved set of components assembles a network integrating signal intensity and directionality to decode the spatial information contained in chemical gradients.

Mathematical modelling of diurnal regulation of carbohydrate allocation by osmo-related processes in plants

Plants synthesize sucrose in source tissues (mainly mature leafs) and supply it for growth of sink tissues (young leafs). Sucrose is derived from photosynthesis during daytime and from starch at night. Because the diurnal regulation of sucrose fluxes is not completely understood, we built a mathematical model designed to reproduce all key experimental observations. For this, assumptions were made about the molecular mechanisms underlying the regulations, which are all motivated by experimental facts. The key regulators in our model are two kinases (SnRK1 and osmo-sensitive kinase OsmK) under the control of the circadian clock. SnRK1 is activated in the night to prepare for regularly occurring carbon-limiting conditions, whereas OsmK is activated during the day to prepare for water deficit, which often occurs in the afternoon. Decrease of SnRK1 and increase of OsmK result in partitioning of carbon towards sucrose to supply growing sink tissues. Concomitantly, increasing levels of the growth regulator trehalose-6-phosphate stimulates the development of new sink tissues and thus sink demand, which further activates sucrose supply in a positive feedback loop. We propose that OsmK acts as a timer to measure the length of the photoperiod and suggest experiments how this hypothesis can be validated.

Function does not follow form in gene regulatory circuits

Gene regulatory circuits are to the cell what arithmetic logic units are to the chip: fundamental components of information processing that map an input onto an output. Gene regulatory circuits come in many different forms, distinct structural configurations that determine who regulates whom. Studies that have focused on the gene expression patterns (functions) of circuits with a given structure (form) have examined just a few structures or gene expression patterns. Here, we use a computational model to exhaustively characterize the gene expression patterns of nearly 17 million three-gene circuits in order to systematically explore the relationship between circuit form and function. Three main conclusions emerge. First, function does not follow form. A circuit of any one structure can have between twelve and nearly thirty thousand distinct gene expression patterns. Second, and conversely, form does not follow function. Most gene expression patterns can be realized by more than one circuit structure. And third, multifunctionality severely constrains circuit form. The number of circuit structures able to drive multiple gene expression patterns decreases rapidly with the number of these patterns. These results indicate that it is generally not possible to infer circuit function from circuit form, or vice versa.

Modularity and predictability in cell signaling and decision making

Cells make decisions to differentiate, divide, or apoptose based on multiple signals of internal and external origin. These decisions are discrete outputs from dynamic networks comprised of signaling pathways. Yet the validity of this decomposition of regulatory proteins into distinct pathways is unclear because many regulatory proteins are pleiotropic and interact through cross-talk with components of other pathways. In addition to the deterministic complexity of interconnected networks, there is stochastic complexity arising from the fluctuations in concentrations of regulatory molecules. Even within a genetically identical population of cells grown in the same environment, cell-to-cell variations in mRNA and protein concentrations can be as high as 50% in yeast and even higher in mammalian cells. Thus, if everything is connected and stochastic, what hope could we have for a quantitative understanding of cellular decisions? Here we discuss the implications of recent advances in genomics, single-cell, and single-cell genomics technology for network modularity and cellular decisions. On the basis of these recent advances, we argue that most gene expression stochasticity and pathway interconnectivity is nonfunctional and that cellular decisions are likely much more predictable than previously expected.

Compartmentalization of a bistable switch enables memory to cross a feedback-driven transition

Cells make accurate decisions in the face of molecular noise and environmental fluctuations by relying not only on present pathway activity, but also on their memory of past signaling dynamics. Once a decision is made, cellular transitions are often rapid and switch-like due to positive feedback loops in the regulatory network. While positive feedback loops are good at promoting switch-like transitions, they are not expected to retain information to inform subsequent decisions. However, this expectation is based on our current understanding of network motifs that accounts for temporal, but not spatial, dynamics. Here, we show how spatial organization of the feedback-driven yeast G1/S switch enables the transmission of memory of past pheromone exposure across this transition. We expect this to be one of many examples where the exquisite spatial organization of the eukaryotic cell enables previously well-characterized network motifs to perform new and unexpected signal processing functions.

How to train your microbe: methods for dynamically characterizing gene networks

Gene networks regulate biological processes dynamically. However, researchers have largely relied upon static perturbations, such as growth media variations and gene knockouts, to elucidate gene network structure and function. Thus, much of the regulation on the path from DNA to phenotype remains poorly understood. Recent studies have utilized improved genetic tools, hardware, and computational control strategies to generate precise temporal perturbations outside and inside of live cells. These experiments have, in turn, provided new insights into the organizing principles of biology. Here, we introduce the major classes of dynamical perturbations that can be used to study gene networks, and discuss technologies available for creating them in a wide range of microbial pathways.

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

Cell fate decisions are critical for life, yet little is known about how their reliability is achieved when signals are noisy and fluctuating with time. In this study, we show that in budding yeast, the decision of cell cycle commitment (Start) is determined by the time integration of its triggering signal Cln3. We further identify the Start repressor, Whi5, as the integrator. The instantaneous kinase activity of Cln3-Cdk1 is recorded over time on the phosphorylated Whi5, and the decision is made only when phosphorylated Whi5 reaches a threshold. Cells adjust the threshold by modulating Whi5 concentration in different nutrient conditions to coordinate growth and division. Our work shows that the strategy of signal integration, which was previously found in decision-making behaviors of animals, is adopted at the cellular level to reduce noise and minimize uncertainty.

ECR-MAPK regulation in liver early development

Early growth is connected to a key link between embryonic development and aging. In this paper, liver gene expression profiles were assayed at postnatal day 22 and week 16 of age. Meanwhile another independent animal experiment and cell culture were carried out for validation. Significance analysis of microarrays, qPCR verification, drug induction/inhibition assays, and metabonomics indicated that alpha-2u globulin (extracellular region)-socs2 (-SH₂-containing signals/receptor tyrosine kinases)-ppp2r2a/pik3c3 (MAPK signaling)-hsd3b5/cav2 (metabolism/organization) plays a vital role in early development. Taken together, early development of male rats is ECR and MAPK-mediated coordination of cancer-like growth and negative regulations. Our data represent the first comprehensive description of early individual development, which could be a valuable basis for understanding the functioning of the gene interaction network of infant development.

Topology and control of the cell-cycle-regulated transcriptional circuitry

Nearly 20% of the budding yeast genome is transcribed periodically during the cell division cycle. The precise temporal execution of this large transcriptional program is controlled by a large interacting network of transcriptional regulators, kinases, and ubiquitin ligases. Historically, this network has been viewed as a collection of four coregulated gene clusters that are associated with each phase of the cell cycle. Although the broad outlines of these gene clusters were described nearly 20 years ago, new technologies have enabled major advances in our understanding of the genes comprising those clusters, their regulation, and the complex regulatory interplay between clusters. More recently, advances are being made in understanding the roles of chromatin in the control of the transcriptional program. We are also beginning to discover important regulatory interactions between the cell-cycle transcriptional program and other cell-cycle regulatory mechanisms such as checkpoints and metabolic networks. Here we review recent advances and contemporary models of the transcriptional network and consider these models in the context of eukaryotic cell-cycle controls.

The linear interplay of intrinsic and extrinsic noises ensures a high accuracy of cell fate selection in budding yeast

To gain insights into the mechanisms of cell fate decision in a noisy environment, the effects of intrinsic and extrinsic noises on cell fate are explored at the single cell level. Specifically, we theoretically define the impulse of Cln1/2 as an indication of cell fates. The strong dependence between the impulse of Cln1/2 and cell fates is exhibited. Based on the simulation results, we illustrate that increasing intrinsic fluctuations causes the parallel shift of the separation ratio of Whi5P but that increasing extrinsic fluctuations leads to the mixture of different cell fates. Our quantitative study also suggests that the strengths of intrinsic and extrinsic noises around an approximate linear model can ensure a high accuracy of cell fate selection. Furthermore, this study demonstrates that the selection of cell fates is an entropy-decreasing process. In addition, we reveal that cell fates are significantly correlated with the range of entropy decreases.

Regulation of cyclin-substrate docking by a G1 arrest signaling pathway and the Cdk inhibitor Far1

Eukaryotic cell division is often regulated by extracellular signals. In budding yeast, signaling from mating pheromones arrests the cell cycle in G1 phase. This arrest requires the protein Far1, which is thought to antagonize the G1/S transition by acting as a Cdk inhibitor (CKI), although the mechanisms remain unresolved. Recent studies found that G1/S cyclins (Cln1 and Cln2) recognize Cdk substrates via specific docking motifs, which promote substrate phosphorylation in vivo. Here, we show that these docking interactions are inhibited by pheromone signaling and that this inhibition requires Far1. Moreover, Far1 mutants that cannot inhibit docking are defective at cell-cycle arrest. Consistent with this arrest function, Far1 outcompetes substrates for association with G1/S cyclins in vivo, and it is present in large excess over G1/S cyclins during the precommitment period where pheromone can impose G1 arrest. Finally, a comparison of substrates that do and do not require docking suggests that Far1 acts as a multimode inhibitor that antagonizes both kinase activity and substrate recognition by Cln1/2-Cdk complexes. Our findings uncover a novel mechanism of Cdk regulation by external signals and shed new light on Far1 function to provide a revised view of cell-cycle arrest in this model system.

The ecology of collective behavior

Networks of local interactions regulate biological systems. Ecological constraints set by resource distribution, operating costs, and the threat of rupture produce similar collective behavior in ants, cells, and gene transcription.

Similar patterns of interaction, such as network motifs and feedback loops, are used in many natural collective processes, probably because they have evolved independently under similar pressures. Here I consider how three environmental constraints may shape the evolution of collective behavior: the patchiness of resources, the operating costs of maintaining the interaction network that produces collective behavior, and the threat of rupture of the network. The ants are a large and successful taxon that have evolved in very diverse environments. Examples from ants provide a starting point for examining more generally the fit between the particular pattern of interaction that regulates activity, and the environment in which it functions.

Negative interactions and feedback regulations are required for transient cellular response

Signal transduction is a process required to conduct information from a receptor to the nucleus. This process is vital for the control of cellular function and fate. The dynamics of signaling activation and inhibition determine processes such as apoptosis, proliferation, and differentiation. Thus, it is important to understand the factors modulating transient and sustained response. To address this question, by applying mathematical approach we have studied the factors which can alter the activation nature of downstream signaling molecules. The factors which we have investigated are loops (feed forward and feedback loops), cross-talk of signal transduction pathways, and the change in the concentration of the signaling molecules. Based on our results we conclude that among these factors feedback loop and the cross-talks which directly inhibit the target protein dominantly controls the transient cellular response.

Genotype to phenotype via network analysis

A prime objective of genomic medicine is the identification of disease-causing mutations and the mechanisms by which such events result in disease. As most disease phenotypes arise not from single genes and proteins but from a complex network of molecular interactions, a priori knowledge about the molecular network serves as a framework for biological inference and data mining. Here we review recent developments at the interface of biological networks and mutation analysis. We examine how mutations may be treated as a perturbation of the molecular interaction network and what insights may be gained from taking this perspective. We review work that aims to transform static networks into rich context-dependent networks and recent attempts to integrate non-coding RNAs into such analysis. Finally, we conclude with an overview of the many challenges and opportunities that lie ahead.

Defining a new vision for the retinoblastoma gene: report from the 3rd International Rb Meeting

The retinoblastoma tumor suppressor (Rb) pathway is mutated in most, if not all human tumors. In the G0/G1 phase, Rb and its family members p107 and p130 inhibit the E2F family of transcription factors. In response to mitogenic signals, Cyclin-dependent kinases (CDKs) phosphorylate Rb family members, which results in the disruption of complexes between Rb and E2F family members and in the transcription of genes essential for S phase progression. Beyond this role in early cell cycle decisions, Rb family members regulate DNA replication and mitosis, chromatin structure, metabolism, cellular differentiation, and cell death. While the RB pathway has been extensively studied in the past three decades, new investigations continue to provide novel insights into basic mechanisms of cancer development and, beyond cancer, help better understand fundamental cellular processes, from plants to mammals. This meeting report summarizes research presented at the recently held 3rd International Rb Meeting.

Start and the restriction point

Commitment to division requires that cells sense, interpret, and respond appropriately to multiple signals. In most eukaryotes, cells commit to division in G1 before DNA replication. Beyond a point, known as Start in yeast and the restriction point in mammals, cells will proceed through the cell cycle despite changes in upstream signals. In metazoans, misregulated G1 control can lead to developmental problems or disease, so it is important to understand how cells decipher the myriad external and internal signals that contribute to the fundamental all-or-none decision to divide. Extensive study of G1 control in the budding yeast Saccharomyces cerevisiae and mammalian culture systems has revealed highly similar networks regulating commitment. However, protein sequences of functional orthologs often indicate a total lack of conservation suggesting significant evolution of G1 control. Here, we review recent studies defining the conserved and diverged features of G1 control and highlight systems-level aspects that may be common to other biological regulatory networks.