Pulsed feedback defers cellular differentiation

Environmental signals induce diverse cellular differentiation programs. In certain systems, cells defer differentiation for extended time periods after the signal appears, proliferating through multiple rounds of cell division before committing to a new fate. How can cells set a deferral time much longer than the cell cycle? Here we study Bacillus subtilis cells that respond to sudden nutrient limitation with multiple rounds of growth and division before differentiating into spores. A well-characterized genetic circuit controls the concentration and phosphorylation of the master regulator Spo0A, which rises to a critical concentration to initiate sporulation. However, it remains unclear how this circuit enables cells to defer sporulation for multiple cell cycles. Using quantitative time-lapse fluorescence microscopy of Spo0A dynamics in individual cells, we observed pulses of Spo0A phosphorylation at a characteristic cell cycle phase. Pulse amplitudes grew systematically and cell-autonomously over multiple cell cycles leading up to sporulation. This pulse growth required a key positive feedback loop involving the sporulation kinases, without which the deferral of sporulation became ultrasensitive to kinase expression. Thus, deferral is controlled by a pulsed positive feedback loop in which kinase expression is activated by pulses of Spo0A phosphorylation. This pulsed positive feedback architecture provides a more robust mechanism for setting deferral times than constitutive kinase expression. Finally, using mathematical modeling, we show how pulsing and time delays together enable “polyphasic” positive feedback, in which different parts of a feedback loop are active at different times. Polyphasic feedback can enable more accurate tuning of long deferral times. Together, these results suggest that Bacillus subtilis uses a pulsed positive feedback loop to implement a “timer” that operates over timescales much longer than a cell cycle.     

Integrating Interactive Computational Modeling in Biology Curricula

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by “building and breaking it” via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the “Vision and Change” call to action in undergraduate biology education by providing a hands-on approach to biology.     

Prey Capture and Phagocytosis in the Choanoflagellate Salpingoeca rosetta

Choanoflagellates are unicellular and colonial aquatic microeukaryotes that capture bacteria using an apical flagellum surrounded by a feeding collar composed of actin-filled microvilli. Flow produced by the apical flagellum drives prey bacteria to the feeding collar for phagocytosis. We report here on the cell biology of prey capture in rosette-shaped colonies and unicellular “thecate” or substrate attached cells from the choanoflagellate S. rosetta. In thecate cells and rosette colonies, phagocytosis initially involves fusion of multiple microvilli, followed by remodeling of the collar membrane to engulf the prey, and transport of engulfed bacteria into the cell. Although both thecate cells and rosette colony cells produce ∼70 nm “collar links” that connect and potentially stabilize adjacent microvilli, only thecate cells were observed to produce a lamellipod-like “collar skirt” that encircles the base of the collar. This study offers insight into the process of prey ingestion by S. rosetta, and provides a context within which to consider potential ecological differences between solitary cells and colonies in choanoflagellates.     

PSYCHIATRY AND THE LAW

In Rex vs. Arnold (1724) it was held that to avail himself of the defense of insanity “a man must be totally deprived of his understanding and memory, so as not to know what he is doing, no more than an infant, a brute, or a wild beast.” Although there has been some modification of this formula in most jurisdictions, the courts still operate under the McNaghten Rule (1843) which is no more logical and actually is more difficult to apply. That such a situation exists in 1956 is a reflection on the indifference of society—and particularly the courts which it elects—as well as on the failure of modern psychiatry to communicate its viewpoint to society. If we are to correct the sad formulae of the “right and wrong” and “policeman at the elbow” tests, we must have more study and better methods of communication in this area.A similar state of confusion exists in the methods of commitment of mentally ill people to psychiatric hospitals. The methods prescribed by law are archaic and cruel—and again reflect the failure of modern psychiatry to communicate its understanding to the legislatures and courts.There are many other areas of conflict between law (which looks to the past for its insights) and psychiatry (which seeks for its concepts in the current scientific advances).     

The Past and Future of Tuberculosis Research

Renewed efforts in tuberculosis (TB) research have led to important new insights into the biology and epidemiology of this devastating disease. Yet, in the face of the modern epidemics of HIV/AIDS, diabetes, and multidrug resistance—all of which contribute to susceptibility to TB—global control of the disease will remain a formidable challenge for years to come. New high-throughput genomics technologies are already contributing to studies of TB''s epidemiology, comparative genomics, evolution, and host–pathogen interaction. We argue here, however, that new multidisciplinary approaches—especially the integration of epidemiology with systems biology in what we call “systems epidemiology”—will be required to eliminate TB.     

The Kinase Regulator Mob1 Acts as a Patterning Protein for Stentor Morphogenesis

Morphogenesis and pattern formation are vital processes in any organism, whether unicellular or multicellular. But in contrast to the developmental biology of plants and animals, the principles of morphogenesis and pattern formation in single cells remain largely unknown. Although all cells develop patterns, they are most obvious in ciliates; hence, we have turned to a classical unicellular model system, the giant ciliate Stentor coeruleus. Here we show that the RNA interference (RNAi) machinery is conserved in Stentor. Using RNAi, we identify the kinase coactivator Mob1—with conserved functions in cell division and morphogenesis from plants to humans—as an asymmetrically localized patterning protein required for global patterning during development and regeneration in Stentor. Our studies reopen the door for Stentor as a model regeneration system.     

Translational systems biology of inflammation

Inflammation is a complex, multi-scale biologic response to stress that is also required for repair and regeneration after injury. Despite the repository of detailed data about the cellular and molecular processes involved in inflammation, including some understanding of its pathophysiology, little progress has been made in treating the severe inflammatory syndrome of sepsis. To address the gap between basic science knowledge and therapy for sepsis, a community of biologists and physicians is using systems biology approaches in hopes of yielding basic insights into the biology of inflammation. “Systems biology” is a discipline that combines experimental discovery with mathematical modeling to aid in the understanding of the dynamic global organization and function of a biologic system (cell to organ to organism). We propose the term translational systems biology for the application of similar tools and engineering principles to biologic systems with the primary goal of optimizing clinical practice. We describe the efforts to use translational systems biology to develop an integrated framework to gain insight into the problem of acute inflammation. Progress in understanding inflammation using translational systems biology tools highlights the promise of this multidisciplinary field. Future advances in understanding complex medical problems are highly dependent on methodological advances and integration of the computational systems biology community with biologists and clinicians.     

Context based mixture model for cell phase identification in automated fluorescence microscopy

Background  

Automated identification of cell cycle phases of individual live cells in a large population captured via automated fluorescence microscopy technique is important for cancer drug discovery and cell cycle studies. Time-lapse fluorescence microscopy images provide an important method to study the cell cycle process under different conditions of perturbation. Existing methods are limited in dealing with such time-lapse data sets while manual analysis is not feasible. This paper presents statistical data analysis and statistical pattern recognition to perform this task.     

Some Formal Approaches to the Analysis of Kinetic Data in Terms of Linear Compartmental Systems

A formal approach to the routine analysis of kinetic data in terms of linear compartmental systems is presented. The methods of analysis are general in that they include much of the theory in common use, such as direct solution of differential equations, integral equations, transfer functions, fitting of data to sums of exponentials, matrix solutions, etc. The key to the formalism presented lies in the fact that a basic operational unit—called “compartment”—has been defined, in terms of which physical and mathematical models as well as input and output functions can be expressed. Additional features for calculating linear combinations of functions and for setting linear dependence relations between parameters add to the versatility of this method. The actual computations for the values of model parameters to yield a least squares fit of the data are performed on a digital computer. A general computer program was developed that permits the routine fitting of data and the evolution of models.     

Cell Lineages and the Logic of Proliferative Control

It is widely accepted that the growth and regeneration of tissues and organs is tightly controlled. Although experimental studies are beginning to reveal molecular mechanisms underlying such control, there is still very little known about the control strategies themselves. Here, we consider how secreted negative feedback factors (“chalones”) may be used to control the output of multistage cell lineages, as exemplified by the actions of GDF11 and activin in a self-renewing neural tissue, the mammalian olfactory epithelium (OE). We begin by specifying performance objectives—what, precisely, is being controlled, and to what degree—and go on to calculate how well different types of feedback configurations, feedback sensitivities, and tissue architectures achieve control. Ultimately, we show that many features of the OE—the number of feedback loops, the cellular processes targeted by feedback, even the location of progenitor cells within the tissue—fit with expectations for the best possible control. In so doing, we also show that certain distinctions that are commonly drawn among cells and molecules—such as whether a cell is a stem cell or transit-amplifying cell, or whether a molecule is a growth inhibitor or stimulator—may be the consequences of control, and not a reflection of intrinsic differences in cellular or molecular character.     

Use of artificial genomes in assessing methods for atypical gene detection

Parametric methods for identifying laterally transferred genes exploit the directional mutational biases unique to each genome. Yet the development of new, more robust methods—as well as the evaluation and proper implementation of existing methods—relies on an arbitrary assessment of performance using real genomes, where the evolutionary histories of genes are not known. We have used the framework of a generalized hidden Markov model to create artificial genomes modeled after genuine genomes. To model a genome, “core” genes—those displaying patterns of mutational biases shared among large numbers of genes—are identified by a novel gene clustering approach based on the Akaike information criterion. Gene models derived from multiple “core” gene clusters are used to generate an artificial genome that models the properties of a genuine genome. Chimeric artificial genomes—representing those having experienced lateral gene transfer—were created by combining genes from multiple artificial genomes, and the performance of the parametric methods for identifying “atypical” genes was assessed directly. We found that a hidden Markov model that included multiple gene models, each trained on sets of genes representing the range of genotypic variability within a genome, could produce artificial genomes that mimicked the properties of genuine genomes. Moreover, different methods for detecting foreign genes performed differently—i.e., they had different sets of strengths and weaknesses—when identifying atypical genes within chimeric artificial genomes.     

An “elite hacker”: Breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity

The year 2011 marked the 40 year anniversary of Richard Nixon signing the National Cancer Act, thus declaring the beginning of the “War on Cancer” in the United States. Whereas we have made tremendous progress toward understanding the genetics of tumors in the past four decades, and in developing enabling technology to dissect the molecular underpinnings of cancer at unprecedented resolution, it is only recently that the important role of the stromal microenvironment has been studied in detail. Cancer is a tissue-specific disease, and it is becoming clear that much of what we know about breast cancer progression parallels the biology of the normal breast differentiation, of which there is still much to learn. In particular, the normal breast and breast tumors share molecular, cellular, systemic and microenvironmental influences necessary for their progression. It is therefore enticing to consider a tumor to be a “rogue hacker”—one who exploits the weaknesses of a normal program for personal benefit. Understanding normal mammary gland biology and its “security vulnerabilities” may thus leave us better equipped to target breast cancer. In this review, we will provide a brief overview of the heterotypic cellular and molecular interactions within the microenvironment of the developing mammary gland that are necessary for functional differentiation, provide evidence suggesting that similar biology—albeit imbalanced and exaggerated—is observed in breast cancer progression particularly during the transition from carcinoma in situ to invasive disease. Lastly we will present evidence suggesting that the multigene signatures currently used to model cancer heterogeneity and clinical outcome largely reflect signaling from a heterogeneous microenvironment—a recurring theme that could potentially be exploited therapeutically.     

A dynamic formin-dependent deep F-actin network in axons

Although actin at neuronal growth cones is well-studied, much less is known about actin organization and dynamics along axon shafts and presynaptic boutons. Using probes that selectively label filamentous-actin (F-actin), we found focal “actin hotspots” along axons—spaced ∼3–4 µm apart—where actin undergoes continuous assembly/disassembly. These foci are a nidus for vigorous actin polymerization, generating long filaments spurting bidirectionally along axons—a phenomenon we call “actin trails.” Super-resolution microscopy reveals intra-axonal deep actin filaments in addition to the subplasmalemmal “actin rings” described recently. F-actin hotspots colocalize with stationary axonal endosomes, and blocking vesicle transport diminishes the actin trails, suggesting mechanistic links between vesicles and F-actin kinetics. Actin trails are formin—but not Arp2/3—dependent and help enrich actin at presynaptic boutons. Finally, formin inhibition dramatically disrupts synaptic recycling. Collectively, available data suggest a two-tier F-actin organization in axons, with stable “actin rings” providing mechanical support to the plasma membrane and dynamic "actin trails" generating a flexible cytoskeletal network with putative physiological roles.     

Computational and Genetic Reduction of a Cell Cycle to Its Simplest,Primordial Components

What are the minimal requirements to sustain an asymmetric cell cycle? Here we use mathematical modelling and forward genetics to reduce an asymmetric cell cycle to its simplest, primordial components. In the Alphaproteobacterium Caulobacter crescentus, cell cycle progression is believed to be controlled by a cyclical genetic circuit comprising four essential master regulators. Unexpectedly, our in silico modelling predicted that one of these regulators, GcrA, is in fact dispensable. We confirmed this experimentally, finding that ΔgcrA cells are viable, but slow-growing and elongated, with the latter mostly due to an insufficiency of a key cell division protein. Furthermore, suppressor analysis showed that another cell cycle regulator, the methyltransferase CcrM, is similarly dispensable with simultaneous gcrA/ccrM disruption ameliorating the cytokinetic and growth defect of ΔgcrA cells. Within the Alphaproteobacteria, gcrA and ccrM are consistently present or absent together, rather than either gene being present alone, suggesting that gcrA/ccrM constitutes an independent, dispensable genetic module. Together our approaches unveil the essential elements of a primordial asymmetric cell cycle that should help illuminate more complex cell cycles.     

The Synthesis Paradigm in Genetics

Experimental genetics with model organisms and mathematically explicit genetic theory are generally considered to be the major paradigms by which progress in genetics is achieved. Here I argue that this view is incomplete and that pivotal advances in genetics—and other fields of biology—are also made by synthesizing disparate threads of extant information rather than generating new information from experiments or formal theory. Because of the explosive expansion of information in numerous “-omics” data banks, and the fragmentation of genetics into numerous subdisciplines, the importance of the synthesis paradigm will likely expand with time.MAJOR advances in the field of genetics have been developed on a foundation supported by three major pillars (i.e., paradigms, by which I mean a framework of basic assumptions, logical approaches, and methodologies), two of which are widely known and appreciated while the third is rarely even acknowledged. The first major paradigm is experimental genetics, especially in the context of model organisms. The work of Thomas H. Morgan and his colleagues at Cal Tech during the early 20th century is a classic example of this approach. A succession of elegant experimental studies by this research team led to the development of the Drosophila melanogaster model system, which Morgan et al. (1915) used to construct the first genomic map that included genes assigned to precise locations on all of an organism’s chromosomes. Their accumulated experimental results also contributed importantly to their book, The Mechanism of Mendelian Heredity (1915), which many consider to be the catalyst that launched the modern era of genetics.The second paradigm is mathematically explicit genetic theory. The succession of genetical theory papers published throughout the first half of the 20th century by Ronald A. Fisher is a classic example of this approach. Fisher’s work reconciled a fundamental rift in the early history of modern genetics—i.e., the genetic approaches of the Mendelians (advocated by William Bateson and Hugo de Vries) vs. the Galtonians (also known as the biometricians, represented in particular by Karl Pearson and Walter F. Weldon)—by showing that Mendelian particulate inheritance could be unified with the quantitative genetics used to analyze continuously varying traits such as height and weight (Fisher 1918). Although Darwin developed the basic framework of evolution, it was Fisher—and contemporary theoreticians Sewall Wright and J. B. S. Haldane—who integrated this qualitative idea into a quantitatively explicit genetic theory that led to the modern synthesis of evolution and launched the field of evolutionary genetics (also known as population genetics and summarized in Fisher’s now classic book, The Genetical Theory of Natural Selection, first published in 1930). Of course, some theory in genetics is not mathematically explicit, such as the “chromosomal theory of inheritance” or the “central dogma.” But this form of theory usually represents the culmination of studies using the experimental genetics paradigm rather than a unique approach to genetics.Most major advances in genetics have been achieved via one, the other, or a combination of these experimental and theoretical paradigms. But there is a well-known exception: Watson and Crick’s discovery of the structure of DNA (Watson and Crick 1953a,b, ∼11,000 combined citations—throughout, numbers of citations are taken from Google Scholar—, and arguably the pivotal publications that launched the modern field of molecular genetics). Watson and Crick used no mathematical genetic theory, nor did they do any critical experiments; instead, they integrated many threads of established information (some unpublished) to deduce the chemical structure of the hereditary material, i.e., the DNA double helix and how this structure could explain gene replication. Although later experiments, such as those of Meselson and Stahl (1958) on DNA replication, would ultimately confirm the deduced structure and replication of DNA that was proposed by Watson and Crick, the pivotal publications of these researchers used neither the experimental nor the theory paradigms of genetics. Their approach exemplifies what I will call the “synthesis paradigm.” Watson and Crick’s work demonstrates that there is actually a trichotomy of approaches—the experimental, theoretical-mathematical, and theoretical-synthetic approaches—that combine like interwoven, reinforcing strands in a cord of historical advances in genetics.In the next few sections I describe other instances in which the synthesis paradigm has been of critical importance in the field of genetics. This set of examples is meant to be illustrative and by no means exhaustive. Next I illustrate how the synthesis paradigm has been of critical importance in other fields of biology. Finally, I describe how a fuller appreciation of the synthesis paradigm can influence the training of the next cohort of geneticists and the career trajectory of current geneticists.     

Dynamics of the endoplasmic reticulum and golgi apparatus during early sea urchin development

The endoplasmic reticulum (ER) and Golgi were labeled by green fluorescent protein chimeras and observed by time-lapse confocal microscopy during the rapid cell cycles of sea urchin embryos. The ER undergoes a cyclical microtubule-dependent accumulation at the mitotic poles and by photobleaching experiments remains continuous through the cell cycle. Finger-like indentations of the nuclear envelope near the mitotic poles appear 2-3 min before the permeability barrier of the nuclear envelope begins to change. This permeability change in turn is approximately 30 s before nuclear envelope breakdown. During interphase, there are many scattered, disconnected Golgi stacks throughout the cytoplasm, which appear as 1- to 2-microm fluorescent spots. The number of Golgi spots begins to decline soon after nuclear envelope breakdown, reaches a minimum soon after cytokinesis, and then rapidly increases. At higher magnification, smaller spots are seen, along with increased fluorescence in the ER. Quantitative measurements, along with nocodazole and photobleaching experiments, are consistent with a redistribution of some of the Golgi to the ER during mitosis. The scattered Golgi coalesce into a single large aggregate during the interphase after the ninth embryonic cleavage; this is likely to be preparatory for secretion of the hatching enzyme during the following cleavage cycle.     

A Fundamental Trade-off in Covalent Switching and Its Circumvention by Enzyme Bifunctionality in Glucose Homeostasis

Covalent modification provides a mechanism for modulating molecular state and regulating physiology. A cycle of competing enzymes that add and remove a single modification can act as a molecular switch between “on” and “off” and has been widely studied as a core motif in systems biology. Here, we exploit the recently developed “linear framework” for time scale separation to determine the general principles of such switches. These methods are not limited to Michaelis-Menten assumptions, and our conclusions hold for enzymes whose mechanisms may be arbitrarily complicated. We show that switching efficiency improves with increasing irreversibility of the enzymes and that the on/off transition occurs when the ratio of enzyme levels reaches a value that depends only on the rate constants. Fluctuations in enzyme levels, which habitually occur due to cellular heterogeneity, can cause flipping back and forth between on and off, leading to incoherent mosaic behavior in tissues, that worsens as switching becomes sharper. This trade-off can be circumvented if enzyme levels are correlated. In particular, if the competing catalytic domains are on the same protein but do not influence each other, the resulting bifunctional enzyme can switch sharply while remaining coherent. In the mammalian liver, the switch between glycolysis and gluconeogenesis is regulated by the bifunctional 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFK-2/FBPase-2). We suggest that bifunctionality of PFK-2/FBPase-2 complements the metabolic zonation of the liver by ensuring coherent switching in response to insulin and glucagon.     

Menstrual Cycle Phase Does Not Predict Political Conservatism

Recent authors have reported a relationship between women''s fertility status, as indexed by menstrual cycle phase, and conservatism in moral, social and political values. We conducted a survey to test for the existence of a relationship between menstrual cycle day and conservatism.2213 women reporting regular menstrual cycles provided data about their political views. Of these women, 2208 provided information about their cycle date, 1260 provided additional evidence of reliability in self-reported cycle date, and of these, 750 also indicated an absence of hormonal disruptors such as recent hormonal contraception use, breastfeeding or pregnancy. Cycle day was used to estimate day-specific fertility rate (probability of conception); political conservatism was measured via direct self-report and via responses to the "Moral Foundations” questionnaire. We also recorded relationship status, which has been reported to interact with menstrual cycle phase in determining political preferences.We found no evidence of a relationship between estimated cyclical fertility changes and conservatism, and no evidence of an interaction between relationship status and cyclical fertility in determining political attitudes. Our findings were robust to multiple inclusion/exclusion criteria and to different methods of estimating fertility and measuring conservatism. In summary, the relationship between cycle-linked reproductive parameters and conservatism may be weaker or less reliable than previously thought.