Any organism is embedded in an environment that changes over time. The timescale for and statistics of environmental change, the precision with which the organism can detect its environment, and the costs and benefits of particular protein expression levels all will affect the suitability of different strategies–such as constitutive expression or graded response–for regulating protein levels in response to environmental inputs. We propose a general framework–here specifically applied to the enzymatic regulation of metabolism in response to changing concentrations of a basic nutrient–to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, respectively, and the costs associated with enzyme production. We use this framework to address three fundamental questions: (i) when a cell should prefer thresholding to a graded response; (ii) when there is a fitness advantage to implementing a Bayesian decision rule; and (iii) when retaining memory of the past provides a selective advantage. We specifically find that: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones. All organisms live in environments that dynamically change in ways that are only partially predictable. The seasons, diurnal cycles, oceanic fluid dynamics, and the progression of food through the human gut, all impose some predictability on common microbial ecosystems. Microbes are also at the whim of random processes  that introduce uncertainty into environmental change. Here, we develop a theoretical framework to analyze how cellular regulatory systems might balance this predictability and uncertainty to most effectively respond to a dynamic environment. We model a simple cellular goal: regulating a single enzyme to maximize the energy generated from a nutrient whose environmental concentration varies. In this context, optimal regulatory strategies are determined by an uncertainty ratio comparing cellular measurement noise and environmental variability. Intermediate levels of uncertainty call for sophisticated Bayesian decision rules, where selective advantage accrues to organisms that incorporate past experience in their inference of the current environmental state. When uncertainty is either high or low, optimal signal processing strategies are comparatively simple: constitutive expression or naive tracking, respectively. This work provides a theoretical basis for interpreting molecular signal processing algorithms and suggests that relative levels of environmental variability and cellular noise affect how microbes should process information. Any organism is embedded in an environment that changes in ways that are typically outside the organism's control and stochastic, yet not entirely unpredictable. In response to such changing environmental conditions, organisms dynamically regulate the expression of their genomes to meet physiological demands For environmental sensing and gene regulation, biomolecular circuits often employ complex information processing and control algorithms Microorganisms occupy a diverse range of environmental niches, so that characteristic time scales of environmental change range over many orders of magnitude Here, we develop a general decision-theoretic framework for deriving optimal regulatory algorithms for a model cellular task–the regulation of expression of a single enzyme in response to a time-varying environmental nutrient concentration Previous studies have postulated a role for Bayesian decision rules in nutrient sensing and studied biochemical implementations of optimal Bayesian sensing strategies in a limited number of circumscribed environmental contexts We consider the cellular task of responding to a time-varying stochastic environmental signal by regulating the expression of a single metabolic enzyme The benefit concave function has convex function has We model the enzyme production cost In this section we ask when should a cell threshold: when should it implement a discrete response or instead produce a graded response to environmental concentrations? We find that the relative convexity of the expression cost function produces a preference for either graded or switch-like regulatory strategies.For perfect sensing of the environment, the optimal regulatory strategy relative to the benefit function, When nutrient concentration is relatively high, tion see . More geit,  see .In this way, optimal regulatory algorithms with perfect measurement fall into two qualitative classes: for a cost function strictly convex relative to benefits, the cell should track the environment with a graded regulatory strategy; and for a cost function strictly concave relative to benefits, the cell should perform thresholded switching between on and off enzyme states. Thus, a discrete or continuous regulatory strategy is optimal depending on the relative curvatures of the enzymatic cost and benefit functions.In this section we ask when there is a fitness advantage to implementing sophisticated Bayesian decision rules, which combine information from present measurement and prior knowledge of environmental statistics. We find such an advantage in contexts of medium measurement imprecision relative to environmental variability, when uncertainty is sufficiently low that individual measurements have informational value, but sufficiently high that prior knowledge is also useful.Cells measure the concentration of environmental nutrients through protein sensors (often membrane-bound receptors). These sensors exist in small copy numbers and are subject to strong thermal conformational fluctuations, thus the cellular measurement apparatus operates stochastically rather than deterministically, providing imperfect measurements of nutrient concentrations averages, not on their variances or higher-order moments. We initially consider environments that vary but are uncorrelated in time, and introduce the prior environmental distribution The cell's regulatory strategy must depend only upon measured concentration For the unsaturated enzyme benefit function [Eq. (1)] with strictly convex costs, Due to the linear dependence of this benefit function on nutrient concentration, the optimal response now depends upon In the presence of measurement noise, Bayes' rule motivates consideration of environmental statistics, encoded in e.g., in the strictly concave cost regime where Expectations preserve convexity, so the basic results under perfect measurement are preserved: First we assume a simple Gaussian distribution of nutrient concentrations. Straightforward calculation reveals that for mean nutrient level where i.e., unresponsiveness to changing measurements. In the intermediate regime, non-degenerate Bayesian decision rule, one that makes use of both prior information and the current measurement. Notice that the quantitative level of optimal enzyme expression is determined by statistical properties of the environment: for When measurement uncertainty is small compared to environmental variability, ement,”   top row We now examine an environmental nutrient distribution with more complex structure, specifically an environment that fluctuates between two dominant conditions, one of abundant nutrient and one of scarce nutrient . Concretated by   top row,Where measurement uncertainty is large compared to environmental variability within a given mode,  regimes  demarcatLarger multimodal Gaussian mixture model  leads to an optimal regulatory strategy that infers the environmental state from a measured concentration of nutrient. When measurement noise is low estimation is not required, and when measurement noise is very high estimation is not possible; in the intermediate regime, optimal regulatory strategies are non-degenerate Bayesian decision rules.In this way, a stochastic environment imposes structure on the optimal sensing strategy through estimation of nutrient levels based on environmental statistics. Prior knowledge of the multimodal nature of the environmental nutrient distribution  relates the quantitative architecture, and hence underlying biochemical parameters, of the optimal sensing apparatus to statistical properties of the environment. For example, the optimal sensing strategy is to threshold the readout into a discrete on or off response in the regime Ref. In this section we ask when should a cell remember: when does a cell benefit from retaining memory of past environmental states? In dynamic contexts, we find that retaining memory produces a fitness advantage for intermediate levels of measurement imprecision, where measurement is sufficiently precise to constrain possible environmental states, but still noisy enough that inference benefits from combining present and past measurements.So far, we have implicitly assumed that a cell does not retain any memory of specific past measurements. But an environment with temporal correlations that persist longer than cellular measurement intervals will reward more sophisticated inference algorithms. Here we address how a cell can optimally combine sequential measurements of a nutrient signal in time to regulate the level of the corresponding metabolic enzyme.In particular, we seek a regulatory strategy We assume that the environmental dynamics are Markovian, and that successive measurements depend only on the current true nutrient via a time-invariant measurement distribution For further concreteness, we specify a mean-reverting diffusive environment with conditional nutrient distribution The linear mean-reversion, quadratic diffusion, and quadratic measurement errors ensure that this estimate is precisely that of a Kalman filter When the conditional variance of nutrients dwarfs the measurement error, Cellular memory of a past measurement some see . In multEq. (11) suggests that optimal regulatory strategies internalize the temporal structure of the environment in the signal-processing apparatus. Namely, ment see , and  deIn the analysis presented here, measurement noise and environmental structure interact to determine the optimal regulatory strategy. In this work we specifically find that: (i) convexity of enzyme expression cost, relative to benefit, influences preferences for thresholding or graded responses; (ii) intermediate levels of uncertainty call for a sophisticated Bayesian decision rule that combines prior information with new measurement; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past.The perspective adopted here provides a decision-theoretic framework for interpreting existing biomolecular signal processing algorithms, by relating optimal response to environmental and cellular statistics in a novel yet intuitive manner. It is easily extensible to provide computational tools for predicting optimal regulatory strategies in complex environments where correlations are derived directly from ecological data. The framework represents a natural classification system that, through continuous variation of dimensionless parameters, relates a range of regulatory strategies that at first glance appear qualitatively distinct. Further exploration of parameter space  a cell constitutively expressing the corresponding metabolic enzyme will outperform a cell regulating enzyme expression. Experiments to test these ideas could compare, in rapidly-changing microfluidics environments, the fitness of synthetic nutrient response pathways designed to implement either constitutive or graded response, with measurement noise titrated via differing steady-state receptor copy numbers due to high- or low-copy number plasmids.Our model system is an enzyme We formulate the cell's regulatory task as choosing the concentration of enzyme that maximizes a function regulatory strategyA Under Michaelis-Menten enzyme kinetics we propose a benefit function We initially consider a model where the environment is changing in an uncorrelated fashion so that at any instant in time, the cell is exposed to the nutrient at concentration First, we find the average value of the payoff function conditioned on This expected payoff depends upon the environmental statistics, Maximizing regulatory strategy. For our specified payoff function with unsaturated enzyme kinetics, We call this function In the name of simplicity, tractability, and interpretability, this model contains a number of simplifying assumptions: the cell can sense and respond to a signal on timescales faster than those on which the environment varies; the metabolic benefit is linear in the enzyme concentration; system cost is only a function of the current level of enzyme; all regulatory mechanisms are equally costly, regardless of their steady-state energy requirements, number of required components, or overall complexity; the cell can set a deterministic enzyme level in response to a given readout level; and we only consider a single enzyme and single nutrient. We also assume simple functional forms throughout this framework in order to derive analytic results, though the qualitative character of these results should be robust to modest variation of the model details.We start with the case of perfect detection, where we immediately see that By contrast, in the strictly concave cost regime, For the full Michaelis-Menten benefit model, the benefit remains linear in Again, when More generally, for any cost and benefit functions that are power laws of the enzyme concentration with If also relative to the benefit function, which is positive for Henceforth, instead of perfect detection we assume an unbiased Gaussian error, whereby where Local optima are found by differentiating with respect to giving for strictly convex costs, We are optimizing the expected payoff, without any concern for variance or higher-order moments of the payoff, which means that the optimal response in a stochastic environment is the same as the optimal response in the deterministic case, but For our specified payoff function, in the strictly convex cost regime, Due to Bayes' rule this expectation In the strictly concave cost regime, A uniform probability of nutrient levels corresponds to an uninformative prior, essentially a constant Here we assume a simple Gaussian distribution of nutrient concentrations, Simple integration shows that the posterior distribution and variance We now assume an equiprobable mixture of two Gaussians, each with the same variance Here, This model is easily extensible to several environmental modes. In this case, the expectation is a weighted sum of terms, one for each Gaussian mode in the mixture. The term corresponding to each mode This model is also trivially generalized to an arbitrary prior over the different modes. For a prior probability Previously, we analyzed an environment where the nutrient signal was uncorrelated in time, so that We proceed similarly to before, but now we derive the average value of the payoff function with respect to both past and current measurements. To this end, we derive an expression for and secondly, that a measurement depends only on the current true nutrient concentration via a time-invariant measurement distribution Given these assumptions, where Thus the expected payoff is As previously, we also note that for our specific payoff function We consider a mean-reverting environment with conditional distribution such that the correlation time, in units of discrete time steps, is As before, we assume a Gaussian measurement error We can extend the expectation to depend on two past measurements in a derivation that is algebraically tedious but conceptually identical to the one above: Figure S1Optimal regulatory strategy varies with environmental variability and measurement imprecision. Blue curves plot optimal regulatory strategy as a function of cellular readout (PDF)Click here for additional data file.Figure S2Optimal regulatory strategy varies with environmental persistence and relative measurement imprecision. Heat maps plot optimal regulatory strategy as a function of present readout (PDF)Click here for additional data file.


Research suggests that these meditations have differential, dissociable effects on a wide range of cognitive (control) processes, such as attentional selection, conflict monitoring, divergent, and convergent thinking. Although research on exactly how the various meditations operate on these processes is still missing, different kinds of meditations are associated with different neural structures and different patterns of electroencephalographic activity. In this review we discuss recent findings on meditation and suggest how the different meditations may affect cognitive processes, and we give suggestions for directions of future research.Meditation is becoming increasingly popular as a topic for scientific research and theories on meditation are becoming ever more specific. We distinguish between what is called  While meditation does seem to reduce stress and to induce a relaxing state of mind, it can also have significant effects on how people perceive and process the world around them and alter the way they regulate attention and emotion. Usually, FAM is the starting point for any novice meditator . During Loving-kindness meditation incorporates elements of both FAM and OMM . MeditatWhereas some meditation techniques require the practitioners to focus their attention on only a certain object or event, other techniques allow any internal or external experiences or sensations to enter awareness. Different meditation techniques might therefore bias the practitioner to either a narrow or broad spotlight of attention. This distinction is thought to be most evident with regard to FAM and OMM. FAM induces a narrow attentional focus due to the highly concentrative nature of the meditation, whereas OMM induces a broader attentional focus by allowing and acknowledging any experiences that might arise during meditation.In a seminal study, A more recent study comparing meditators (trained in mindfulness-based stress-reduction) to non-meditators found that meditators show evidence of more accurate and efficient visual attention . MeditatElectrophysiological evidence for meditation-induced improvements in attention comes from a recent study in which Vipassana meditators performed an auditory oddball task before and after meditation (in one session) and random thinking  was associated with increased functional connectivity between the dorsal attention network, the Default Mode Network and the right prefrontal cortex . Thus, mA fundamental skill acquired through meditation is the ability to monitor the attentional focus in order to “redirect it” in the case of conflicting thoughts or external events. Not surprisingly, several studies have already shown improvements in conflict monitoring after meditation. Further evidence for improvements in conflict monitoring come from a study investigating the effect of 6-week long FAM trainig (versus relaxation training and a waiting-list group) on a discrimination task intended to investigate the relationship between attentional load and emotional processing . ParticiIn a study of Improved conflict monitoring does not necessarily entail increased brain activity. B receptor-mediated inhibitory neurotransmission and GABAA receptor-mediated inhibitory neurotransmission  or cartoon (for the non-meditators), respectively, measuring GABAsmission . Given tctivity” , p. 400.The scientific evidence regarding the connection between meditation and creativity is inconsistent. While some studies support a strong positive impact of meditation practice on creativity , others Research on meditation is still in its infancy but our understanding of the underlying functional and neural mechanisms is steadily increasing. However, a serious shortcoming in the current literature is the lack of studies that systematically distinguish between and compare different kinds of meditation on various cognitive, affective or executive control tasks—a criticism that applies to neuroscientific studies in particular. Further progress will require a better understanding of the functional aims of particular meditation techniques and their strategies to achieve them. It will also be important to more systematically assess short- and long-term effects of meditation, as well as the (not yet understood) impact of meditation experience (as present in practitioners but not novices). For instance, several approaches (like Buddhism) favor a particular sequence of acquiring meditation skills (from FAM to OMM) but evidence that this sequence actually matters is lacking. Moreover, the neural mechanisms underlying meditation effects are not well understood. It might be interesting that the three main research topics we have covered in the present review  imply the operation of extended neural networks, which might suggest that meditation operates on neural communication, perhaps by impacting neurotransmitter systems. Finally, it may be interesting to consider individual differences more systematically. If meditation really affects interactions between functional and neural networks, it makes sense to assume that the net effect of meditation of performance depends on the pre-experimental performance level of the individual—be it in terms of compensation (so that worse performers benefit more) or predisposition (so that some are more sensitive to meditation interventions).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Brachionus calyciflorus as a predator and the preySynura petersenii, a colony-forming alga that exhibits genetic variation in its propensity to form colonies and colony size (larger colonies are a defense against predators). Prey populations of either low initial genetic diversity and low adaptive capacity or high initial genetic diversity and high adaptive capacity were crossed with predator presence and absence. Dynamics measured over the last 127 days of the 167-day experiment revealed no effects of initial prey genetic diversity on the average abundance or temporal variability of predator populations. However, genetic diversity and predator presence/absence interactively affected prey population abundance and stability; diversity of prey had no effects in the absence of predators but stabilized dynamics and increased total prey abundance in the presence of predators. The size structure of the genetically diverse prey populations diverged from single strain populations in the presence of predators, showing increases in colony size and in the relative abundance of cells found in colonies. Our work sheds light on the adaptive value of colony formation and supports the general view that genetic diversity and intraspecific trait variation of prey can play a vital role in the short-term dynamics and stability of planktonic predator-prey systems.Heterogeneity among prey in their susceptibility to predation is a potentially important stabilizer of predator-prey interactions, reducing the magnitude of population oscillations and enhancing total prey population abundance. When microevolutionary responses of prey populations occur at time scales comparable to population dynamics, adaptive responses in prey defense can, in theory, stabilize predator-prey dynamics and reduce top-down effects on prey abundance. While experiments have tested these predictions, less explored are the consequences of the evolution of prey phenotypes that can persist in both vulnerable and invulnerable classes. We tested this experimentally using a laboratory aquatic system composed of the rotifer Prey heterogeneity can mediate trophic-level responses to enrichment and weaken top-down limitation of prey communities by facilitating numerical dominance by defended prey12. Such shifts in dominance can have significant dynamic consequences, potentially reducing the propensity and severity of predator-prey oscillations and stabilizing community dynamics9. While empirical research has largely focused on the consequences of interspecific variation in prey edibility, a growing body of experiments has begun to highlight the dynamic consequences of intraspecific trait variation. When prey populations exhibit phenotypic variation in their susceptibility to predators and show rapid adaptive responses to predation pressure, they can fundamentally alter the strength and dynamic consequences of their interactions with their consumers18.A large body of theoretical and empirical work has shown that the presence of variation among prey in their susceptibility to predation can have profound impacts on the structure and dynamics of predator-prey communities22. Such oscillatory dynamics become more probable and increase in amplitude with increasing prey carrying capacity21. Inclusion of prey heterogeneity in the form of species that are defended from predation can in theory stabilize predator-prey cycles. This readily occurs when prey species trade off their ability to compete for shared resources with their capacity to resist predation. In such instances, predators can facilitate the invasion and persistence of defended prey which, in turn, siphon resources from more edible species, reducing their carrying capacity. This can, in some cases, decrease the amplitude of predator-edible prey cycles or move systems from periodic to point attractors23. Predator-mediated increases in the relative abundance of defended prey may also weaken top-down limitation of trophic-level abundance causing an increase in total prey abundance relative to prey community’s lacking trait heterogeneity12.The effects of prey heterogeneity on predator-prey dynamics has been extensively explored in the context of endogenously driven population cycles. Cycles are a common feature of simple, two-species predator-prey models that incorporate nonlinear functional responses24. Several models have also explored how adaptive responses in prey defense may impact predator-prey dynamics and stability26. These demonstrate the capacity for prey evolution to dramatically alter predator-prey dynamics but stabilization is not a generalizable prediction. While adaptive responses in prey defense may stabilize predator or prey populations under certain conditions24, evolution can also give rise to destabilization of predator-prey cycles and enhanced extinction probability26.While the abovementioned models were developed with the intent of understanding the dynamic consequences of heterogeneity among prey species, their general predictions may, under certain conditions, apply to heterogeneity that occurs within species. For instance, models of trophic structure that incorporate prey evolutionary dynamics show that heritable variation in defense against predators may allow prey populations to adaptively respond to predation pressure, shifting regulation of prey populations from top-down control to stronger bottom-up control27. Moreover, previous experiments have only considered phenotypes or species with fixed traits. For many organisms, ecological strategies may involve transitions between dynamic classes that vary in their susceptibility to predators, with variation among phenotypes consisting of variation in state transition rates or degree of invulnerability. This could apply to organisms that change behavioral/physiological states or who move in and out of spatial refuges. It could also occur with colony-forming organisms in which colonies of increasing size are more resistant to predators. Prior work has shown that such prey strategies can stabilize predator-prey cycles1. However, this has not been examined within an evolutionary context.Only a handful of studies have attempted to address the dynamic consequences of intraspecific variability in prey edibility using direct manipulations in which prey evolution was either suppressed xor promotedBrachionus calyciflorus and the algal-preySynura petersenii, in which the potential for prey evolution was either enhanced or reduced through direct manipulations of initial prey genetic diversity. Our study differed from prior work in its use of an algal-prey species that can transition between a vulnerable and predator-resistant class.Synura petersenii is a common freshwater flagellate that may transition between two states: either free-living cells (which are more susceptible to zooplankton predators) or as swimming colonies (which are less susceptible to zooplankton feeding due to their larger size). Reproduction can occur in either the free-living state or in the colony state through binary fission. The strains ofS. petersenii used in our study exhibit heritable variation in their propensity to form colonies and their degree of vulnerability when in the colony state due to variation in colony size . Five strains ofSynura were used in the experiment, four of which  were obtained from UTEX  and one (CBS) from Carolina Biological Supply .Synura stock cultures were initiated with a single cell isolated from serial dilutions in sterile medium to ensure that all stocks were initially isogenic. All fiveSynura strains produced populations composed of a mix of single cells and colonies when under semi-continuous culture conditions. However, short-term trait assays revealed significant genetic variation among the strains in population densities, colony size (number of cells per colony), and the relative abundance of total cells found in colony form . The treatments withBrachionus present were replicated four times; treatments withoutBrachionus were replicated three times. At the initiation of the experiment, flasks were first inoculated with their respectiveSynura strains from stock cultures. The high genetic diversity treatment received 20 cells/mL of each of the five strains while the low diversity treatment received a single strain at 100 cells/mL. Thus, totalSynura density added was kept constant at 100 cells/mL across treatments. While the five strains were added at lower initial densities in the high genetic diversity treatment, each flask received a total of 8000 cells of each strain. Hence, the probability of losing a strain through demographic stochasticity and genetic drift at the initiation of the experiment was low.Synura populations were allowed to grow in the absence of predators for seven days at which time 10Brachionus adults were added to each plus predator treatment. We refer to this as day 0 of the experiment.Brachionus populations were allowed to grow for 12 days (with periodic medium replacement) at which time sampling was initiated.All experimental materials were autoclave-sterilized prior to use. Experimental containers consisted of 500mL flasks filled with 400mL of COMBO mediumBrachionus was enumerated using a stereomicroscope whileSynura was enumerated using a CASY particle counter . Maximum cell diameter ofSynura in our cultures ranged between 6–10µm (mean=7.9µm); we found no significant differences among our strains in mean maximum diameter. Consequently, we programmed the CASY to perform total counts and counts of particles below 10.5µm mean diameter as an estimate of the density of free living cells. Colony densities were then calculated by subtracting single cell counts from totals. To measure the density of cells in colonies, we multiplied the colony counts by estimates of the mean number of cells per colony for each treatment replicate. Estimates of cells per colony were performed at four time points during the experiment: at the initiation of the experiment, on day 30, day 97 and at the end of the experiment. To obtain estimates, subsamples of phytoplankton from each replicate were preserved in acid Lugols solution and counts performed using a compound microscope. We counted cells/colony for up to 25 haphazardly chosen colonies per sample and averaged the values. Because we did not have mean colony size estimates for all dates, we time-averaged the estimates of cells/colony over days 30 to 167 to create conversion constants for each replicate prior to multiplying by the colony counts. This should have provided conservative estimates of treatments effects since treatments had not completely diverged by the day 30 sample. Total cell density was calculated by summing free-living cell densities with estimates of the density of cells found in colonies.Sampling occurred every 2–3 days up to day 167, the final day of the experiment. To sample the experiment, flasks were first gently swirled to homogenize their contents and 12.5% of the volume (50mL) was poured into a sample bottle, which served as both a zooplankton and phytoplankton sample. Removed medium was replaced with sterile COMBO medium. Thus, the experiment was maintained under semi-continuous culture conditions.Brachionus populations in the low diversity treatment rapidly went extinct in all replicates of the LB239, LB2403, LB2405, and LB2406 strains. We consequently discontinued sampling of these monocultures and focused on the CBS strain for the low genetic diversity treatment.Brachionus populations exhibited an initial exponential growth phase followed by a population decline between days 0 and 40 before settling into more regular population oscillations. To remove the influence of initial transitory dynamics we analyzed data over days 51 to 167. Significant linear trends over time inSynura andBrachionus densities were evident in several replicates (see Results). To remove the influence of temporal trends on measures of temporal variability, we first performed linear regressions of log transformed densities versus time for each replicate for both species. Mean absolute values of the regression residuals were then used as measures of temporal variability (an inverse measure of stability). Analyses of meanBrachionus andSynura densities were performed on log10 transformed values averaged over days 51 to 167. To analyze changes in the degree of colony formation, we examined colony densities and the relative abundance of cells found in colonies . Response variables were analyzed using ANOVA. Because replication was not equal among replicates, we used type III sums of squares and max t-tests for post hoc comparisons, which are robust to unbalanced designs and non-normal data32. All response variables met assumptions of normality using Lilliefor’s test. Statistics were performed inR version 2.1533. Code for running max t-tests can be found in32.Brachionus populations persisted in all high genetic diversity treatments. However, populations of the zooplankton failed to establish in all low diversity replicates that were composed of the LB239, LB2403, LB2405, and LB2406 genotypes (sampling of these monocultures was discontinued).Brachionus also went extinct mid-experiment in one low genetic diversity replicate containing the CBS strain; we have removed this replicate from all analyses.Brachionus dynamics for all replicates in the presence of either low initial genetic diversity (Brachionus densities over time in one low genetic diversity replicate (p=0.02). Three of four high genetic diversity replicates exhibited significant negative trends in logBrachionus densities over time . Examining regression residuals,Synura genetic diversity had no effect on detrended temporal variability ofBrachionus . Effects of genetic diversity onSynura stability were only strongly evident in the presence ofBrachionus, significantly decreasing temporal variability in the high genetic diversity treatment relative to low genetic diversity . Genetic diversity andBrachionus presence/absence interactively affected temporal variability of colony cell abundances . Genetic diversity reduced temporal variability in the presence  and absence ofBrachionus , but effects were stronger whenBrachionus was present . WhileBrachionus presence/absence had no effects on mean cell densities in the high genetic diversity treatment  but no main effect of genetic diversity or interaction were detected . While the number of colonies was unaffected by initial genetic diversity, colony size (number of cells per colony) varied greatly between diversity treatments . Colony size in the high genetic diversity treatment and in the presence ofBrachionus was greater compared to all other treatment combinations . Colony size in the high genetic diversity treatment withoutBrachionus was also significantly greater than both low genetic diversity treatments . In the low genetic diversity treatment, no effect ofBrachionus presence/absence was detected . Effects on colony size were also apparent when examining the relative number of cells in colonies, which increased greatly in the presence ofBrachionus and high genetic diversity . There was no difference between low and high genetic diversity treatments whenBrachionus was not present  but a strong positive effect ofSynura genetic diversity in the presence ofBrachionus  examining phenotypic variation among the five genotypes of Synura used in the experimentClick here for additional data file.Time series of mean number of cells per Synura colony for all treatments and replicatesClick here for additional data file.23 – a prediction that has garnered some empirical support from studies that have manipulated prey species composition35 and clonal composition15. Our work further demonstrates that intraspecific variation can stabilize dynamics when prey persist in different dynamic classes that vary in predator resistance. The mechanisms that can give rise to vulnerable-invulnerable class structures within prey populations are diverse and include refuge use, inter-individual variation in behavioral or physiological states, and spatial variation in predation pressure1. Thus, our general findings may have broader applicability beyond planktonic systems of colony-forming prey.We found clear evidence that the presence of intraspecific trait heterogeneity can positively impact the stability and abundance of prey populations when in the presence of predators. These effects were linked to increases in the degree of aggregation of prey individuals into colonies; diverse prey populations produced larger colonies and a greater relative abundance of cells found in colony form when predators were present. Our results bear many similarities to prior studies that have examined the dynamic consequences of interspecific variation in prey defense against predators. As outlined in our Introduction, several models have shown that the presence of weakly interacting prey can stabilize dynamics by shunting resources away from more edible forms and subsequently reducing the amplitude of predator-edible prey oscillations25. For example, Hairston, Ellner and colleagues have examined the dynamic consequences of evolutionary responses among prey using models and an experimental system composed ofBrachionus calyciflorus and unicellular green algae as prey17. They have shown both theoretically and experimentally that rapid prey adaption in prey edibility can have significant effects on predator-prey dynamics, though effects are not always stabilizing and dependent on the degree of prey phenotypic variation present and the strength of trade-offs among phenotypes in anti-predator strategies and competitive ability for shared resources. When predator-resistance is effective but costly to defended phenotypes, rapid prey adaptation can induce large predator-prey oscillations and destabilization18. In contrast, when defense against predators is effective but costs in competitive ability are low, prey adaptation can result in cryptic prey cycles in which predators continue to oscillate and total prey abundance is stabilized as edible and predator-resistant phenotypes oscillate out of phase of each other18. The production of cryptic cycles via rapid prey adaptation shows a passing similarity to our results, in which high genetic diversity had no effects on predator stability but led to stabilization of totalSynura abundance in the presence ofBrachionus. Because our sampling intervals were uneven, spanning 2 or 3 days, we could not examine covariation between free-living cells and colony cell abundances using traditional cross-correlation analysis. However, visual examination of detrended abundances of free-livingSynura cells and colony cells over time revealed no strong support for asynchronous oscillations between the two groups  for the low diversity treatment. This is an approach that has been used in prior experiments in which dynamics in the presence of a highly edible prey phenotype are contrasted with dynamics in which the edible prey has been supplemented with additional phenotypes that vary in their susceptibility to predatorsstrains . The onlstrains , which l40. A hurdle in achieving this initial transition is the fitness costs associated with colony formation such as reductions in competitive ability, reproductive rates or buoyancy. Our work supports the general idea that colony formation and large colony size provide a selective advantage in the presence of predators and a disadvantage when predators are absent and resource competition is strong. This finding complements previous studies that have shown similar effects of predators on colony formation in unicellular algae41 and supports the general hypothesis that a driver in the early evolution of multicellularity was the emergence of heterotrophic life forms and phagotrophy – a transition point where the disadvantages of cellular aggregation began to be outweighed by the advantages of increasing size and predator escape29. Our study also adds to a growing body of experiments demonstrating the effects of rapid evolutionary change on the dynamics of consumer-resource interactions42 and the strength of top-down control of prey abundance37. How such effects translate to natural communities remains largely unresolved; the majority of prior experiments, including ours, have utilized highly simplified laboratory settings with a minimal number of interacting species. Moreover, the consequences of coevolutionary responses between predator and prey populations on ecological dynamics have not been deeply explored. Natural prey populations are of course exposed to multiple species of predators and embedded in prey communities with a large degree of interspecific variation in competitive ability and defense against predators. Understanding the dynamic consequences of evolution and coevolution within the context of complex communities remains a daunting challenge in ecology but an exciting avenue for future exploration.Cellular aggregation is viewed as an evolutionary stepping stone between unicellular and multicellular life forms This article shows how increasing genetic variation in prey can stabilize the dynamics, especially since predator can barely establish in communities without variability in prey. This last finding is by far the strongest and I think that it adds substantially to a current important topic. A second relevant finding is that, despite having only a single strain with low variability, the high genetic variability replicates had also more stable dynamics than the one single strain.The finding that colony formation was linked to predator presence and that there was a trend in which colony formation increased through time also provides a hint on how multicellularity evolved.However, unfortunately I do not think that this article provides convincing evidence of an evolutionary response of defense through colony formation as the authors claim. First, in their preliminary assays the authors did not combine the different strains to see how they form colonies when different strains are present in the same habitat. We do not know if they are able to combine and to cooperate with other strains (at least with the information provided) and if there are emergent patterns of colony formation when more than one strain is combined.The findings that defense (aggregative behaviour) increase when predators are present could be just the result of complex patterns of (plastic) cooperation among strains which change through time, for instance as a response to persistent predation risk. Assays at the end of the experiment to test if after removing predators, colonies were still maintained at substantially high rates (e.g. as in strain LB2405) would have been a convincing evidence for adaptive evolution ocurring during the dynamics.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. per se, as opposed to the identity effects of this individual genotype. I agree with the authors that it is a major limitation in interpreting this experiment.The authors of this study performed a laboratory mesocosm experiment that sought to address the role of intraspecific variation in predator-prey dynamics. While the underlying questions presented an interesting and relevant avenue of research, four of the five clonal lines went extinct in their single-genotype treatment.  As a result, their contrasts between low and high prey genetic diversity were performed with a single genotype (CBS strain). Consequently, it is unclear to me whether conclusions could be drawn about the consequences of genetic diversityI have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. This paper demonstrates that prey heterogeneity stabilizes prey population dynamics in an experimental predator-prey system. It should, however, be noted that if this happens via the better-defended prey shunting away resources from the edible prey, then the density of the predator should be lower in the high-prey-diversity treatment. But, according to Fig 3B, this is not the case.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.


This article reviews the literature on sex-specific strategy use in cognitive tasks with the aim to carve out a link between sex differences in different cognitive tasks. I conclude that male strategies are commonly holistic and oriented toward global stimulus aspects, while female strategies are commonly decomposed and oriented toward local stimulus aspects. Thus, the strategies observed in different tasks, may depend on sex differences in attentional focus and hence sex differences in global-local processing. I hypothesize that strategy use may be sex hormone dependent and hence subject to change over the menstrual cycle as evidenced by findings in global-local processing and emotional memory. Furthermore, I propose sex hormonal modulation of hemispheric asymmetries as one possible neural substrate for this theory, thereby building on older theories, emphasizing the importance of sex differences in brain lateralization. The ideas described in the current article represent a perspective toward a unifying approach to the study of sex differences in cognition and their neural correlates. For decades it has been debated, whether men and women differ in specific cognitive abilities  for sex differences in verbal functions across 165 studies using different verbal tasks. However, whether overall performance differences between men and women exist, does not explain why and how cognition differs between the sexes.However, several of these findings have been questioned by theorists arguing that sex differences are overall small and negligible and within-group variation is stronger than the variation between groups Hyde, . For exaFirst, there is an increasing interest in the actions of sex hormones on the brain , while women tend to switch more often between different categories .Perceptual global-local processing is traditionally studied using hierarchical stimuli (Navon paradigm), i.e., a global structure made up of local parts Navon, . These sIf sex differences in cognitive tasks are based on sex differences in attentional focus, these differences should be apparent in a Navon paradigm. Indeed several findings have been published that support this view. Using a divided attention paradigm, a local advantage has been demonstrated in women that was absent in men  or social  factors have been identified that can affect the size of sex differences in cognitive tasks (e.g., Hausmann et al., Results from visual hemifield (e.g., Robertson and Lamb, Hemispheric asymmetries have also been assessed for several of the cognitive functions discussed above as being subject to sex-specific strategy use (for reviews see e.g., Wada, Furthermore, sex differences in brain lateralization have received much attention. Some authors argue that hemispheric asymmetries are more pronounced in men than in women and that a stronger variation in hemispheric asymmetries is apparent in women as compared to men (for reviews see McGlone, progesterone-mediated inter-hemispheric decoupling (Hausmann and Gunturkun, In that respect it has been demonstrated that the lateralization of brain functions is particularly reduced during the luteal cycle phase, when a woman's estradiol and progesterone levels are high (Hausmann and Gunturkun, Other theories stress, that some sex hormones may enhance the functioning and intra-hemispheric integration of a particular hemisphere (e.g., Hampson, While a complete picture of how sex hormones interact with inter-hemispheric communication has yet to emerge, several results indicate that sex hormones modulate inter-hemispheric communication (see Hausmann and Bayer, In summary, it has been found, that sex specific strategies share several features over different cognitive tasks and can be described as global/holistic in men and local/decomposed in women and linked to sex-differences in global-local processing. I hypothesized that sex differences in the lateralization of brain functions accompany these strategies as a result of sex hormone modulation of transcallosal neurotransmission. Empirical evidence linking strategy to lateralization and demonstrating hormone-dependent modulation of strategies as well as lateralization is still lacking for several of the tasks described. This shifts the emphasis from a descriptive comparison of men and women to the question how sex hormones modulate cognition as a whole and can only be answered by an adequate understanding of the changes occurring over the course of the menstrual cycle. The idea of the corpus callosum, gating attentional focus and thereby guiding strategy use in a variety of cognitive tasks represents a perspective toward a link between sex differences in different cognitive tasks.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Both inherited and sporadic mutations can give rise to a plethora of human diseases. Through myriad diverse cellular processes, sporadic mutations can arise through a failure to accurately replicate the genetic code or by inaccurate separation of duplicated chromosomes into daughter cells. The human genome has therefore evolved to encode a large number of proteins that work together with regulators of the cell cycle to ensure that it remains error-free. This is collectively known as the DNA damage response (DDR), and genome stability mechanisms involve a complex network of signalling and processing factors that ensure redundancy and adaptability of these systems. The importance of genome stability mechanisms is best illustrated by the dramatic increased risk of cancer in individuals with underlying disruption to genome maintenance mechanisms. Cilia are microtubule-based sensory organelles present on most vertebrate cells, where they facilitate transduction of external signals into the cell. When not embedded within the specialised ciliary membrane, components of the primary cilium’s basal body help form the microtubule organising centre that controls cellular trafficking and the mitotic segregation of chromosomes. Ciliopathies are a collection of diseases associated with functional disruption to cilia function through a variety of different mechanisms. Ciliopathy phenotypes can vary widely, and although some cellular overgrowth phenotypes are prevalent in a subset of ciliopathies, an increased risk of cancer is not noted as a clinical feature. However, recent studies have identified surprising genetic and functional links between cilia-associated proteins and genome maintenance factors. The purpose of this mini-review is to therefore highlight some of these discoveries and discuss their implications with regards to functional crosstalk between the DDR and ciliogenesis pathways, and how this may impact on the development of human disease. Recent work from several groups has strengthened the ever-expanding functional links between the DNA damage response (DDR) and ciliogenesis. Given that both the DDR and primary ciliogenesis are stress response mechanisms that are inextricably linked to the cell cycle (see below), then these findings are perhaps not too unexpected in the context of their biological function. Furthermore, centrioles, which can help govern genome stability in proliferating cells through correct microtubule organisation and accurate chromosome segregation, also form the basal body of primary cilia within quiescent cells. However, defects in DDR/genome stability factors are traditionally associated with inherited cancer-predisposing diseases syndromes, whereas patients with ciliopathies do not have an increased risk of cancer development. This makes recent findings that mutations in some DDR proteins are causal for a subset of human ciliopathies all the more intriguing. The following sections will therefore give a brief overview of the recently discovered genetic and functional links between DDR and ciliogenesis. We highlight key proteins identified to date that have dual roles in these biological processes.DNA within cells is damaged on a daily basis from both exogenous sources e.g. UV radiation from the sun or carcinogens within tobacco smoke, and from endogenous sources e.g. metabolic by-products, errors introduced during DNA replication, or by chromosome segregation defects during mitosis . In ordeThe centrosome acts as the major site of microtubule nucleation and organisation in both interphasic and mitotic cells, and forms the basis of the basal body during ciliogenesis (see below). It consists of two orthogonally positioned, cylindrically shaped structures known as centrioles, which are surrounded by an electron-dense matrix termed the pericentriolar material (PCM) and acts as an organised scaffold that facilitates protein recruitment to the centrosome. Associated with the PCM are numerous particles termed centriolar satellites, which contain many components of the PCM and other centrosomal proteins –17. The Given the important roles of the centrosome within the cell and functional overlap with DDR (see above), it is perhaps not too surprising that defects in centrosome-associated factors that function in DDR processes give rise to a range of human inherited disorders , 25, 26 Functional links between the DDR and centrosomes have been previously inferred by the centrosomal localisation of several DDR factors including the DNA repair proteins BRCA1, BRCA2, PARP1 and NBS1; the DDR signalling kinases ATM, CHK1 and CHK2; and the cell cycle checkpoint and transcriptional regulator TP53 , 37. HowInteractions between centrosome-associated and DDR proteins can also occur in response to exogenous stress. For example, the centrosomal and ciliogenesis-promoting protein CEP164  can give rise to replication stress which can, in turn, lead to aberrant centrosome duplication and maturation processes. As such, heightened replication stress may be a common source of disrupted centrosome function in cancer, and aberrant cilia function in ciliopathies.FAN1 or MRE11, it is too early to determine if these patients have an increased risk of developing cancer. Given that mutations in both these proteins can give rise to various cancers (see above), one may predict that these ciliopathy patients may have a heightened risk of developing cancer compared with the general population and some other ciliopathy cohorts. For these conditions, pathogenic mechanisms of replication stress leading to DNA damage, concomitant with or upstream of primary cilia function, are an area of exciting future research. Finally, since ciliogenesis and replication stress are potentially reversible with small molecule approaches, these findings also reveal new therapeutic intervention opportunities as possible treatment regimes for these diseases.The majority of human cells are ciliated with the cilium acting as a signalling hub for several interconnected stress response pathways, which are in constant communication with the DNA damage response pathways and cell cycle regulators. Recent discoveries demonstrating that autophagy and ciliogenesis can co-regulate each other, and that autophagy is responsive to oxidative stress/DNA damage and can regulate DNA repair processes, further draw links between primary cilia and the DDR. Such functional interplay has implications for human disease, which is highlighted by the recent discoveries of mutations in proteins, traditionally thought to be solely involved in DNA repair processes, being causative for a subset of human ciliopathies with degenerative diseases of the kidney and retina. With the advent of next-generation sequencing of larger clinical cohorts, it will also be interesting to see if additional DDR factors and autophagy factors are implicated in ciliopathies, and if dysregulation in any cilia-associated factors is associated with an increased risk of cancer development and progression. Indeed, given the young age and small cohort of current ciliopathy patients with causative mutations in either


This process occurs during the progression of cancer to metastatic disease, and is also associated with recurrence as conventional therapies fail to eliminate the minority of resistant tumor cells that have undergone EMT. Brachyury is a transcription factor that controls EMT during development, and we have previously reported that brachyury is aberrantly overexpressed in various human cancers where it promotes tumor cell EMT, metastatic dissemination, and resistance to conventional therapies. These studies led to the development of brachyury-based antitumor vaccine approaches that are currently in Phase I trials. However, we have recently shown that very high expression of brachyury can protect against caspase-dependent immune cell-mediated cytotoxicity . In seek


The eukaryotic cell nucleus houses an organism’s genome and is the location within the cell where all signaling induced and development-driven gene expression programs are ultimately specified. The genome is enclosed and separated from the cytoplasm by the nuclear envelope (NE), a double-lipid membrane bilayer, which contains a large variety of trans-membrane and associated protein complexes. In recent years, research regarding multiple aspects of the cell nucleus points to a highly dynamic and coordinated concert of efforts between chromatin and the NE in regulation of gene expression. Details of how this concert is orchestrated and how it directs cell differentiation and disease are coming to light at a rapid pace. Here we review existing and emerging concepts of how interactions between the genome and the NE may contribute to tissue specific gene expression programs to determine cell fate. Figure 1). Microscopic visualization of DNA stains in ESC nuclei show diffuse staining indicative of a generally open chromatin state (Pluripotent embryonic stem cells (ESCs) from many organisms display strikingly different chromatin structure and overall nuclear architecture when compared with differentiated cells , while Lamin B1 and B2 are transcribed from distinct genes  of the NE . The lamThe B type Lamins (B1 and B2) are expressed in all cell types, while expression of Lamins A and C varies with cell type and developmental stage . ImmunofLamin A (LMNA) gene, which lead to an array of serious diseases called laminopathies, including cardiomyopathy, muscular dystrophy, lipodystropy, neuropathy and progeria , and support the notion that Lamins play functional roles in cell differentiation, as discussed further below.Further supporting separate roles for A and B type Lamins, studies of Lamin filaments in amphibian oocytes and HeLa cells indicate that Lamins A, B and C form discrete, but interconnected, lattice structures with differing physical properties . In agreprogeria . Togethelarge organized chromatin K domains” (LOCKS) grows from 17.5–24% in pluripotent human stem cells to 39.3–44.8% in differentiated cell lines (Lamin B1 Associated Chromatin Domains (LADS), exhibits a significant overlap between LOCKS and LADs, which supports a role for Lamin B1 in the peripheral localization of these heterochromatic domains . They further show this loss and the subsequent chromatin rearrangements coincide with terminal differentiation of the rod cells. Strikingly, the inversion phenotype was successfully recapitulated experimentally in additional cell types, such as the hair follicle (which does not express Lamin A/C), using LBR null mice, and examination of double null (Lbr-/- Lmna-/-) mouse pups indeed showed an inverted phenotype in all post-mitotic cell types studied. Conversely, artificially maintaining expression of LBR, but not Lamin C in these cells was enough to prevent chromatin inversion, suggesting that Lamin C does not bind chromatin directly but perhaps via other nuclear envelope associated proteins such as LEM domain proteins (discussed further below). Although it is not presently clear how the conventional versus the inverted heterochromatin architecture affects cell type specific gene expression, these results support the notion that Lamins B and A/C are needed to position heterochromatin in a cell type specific manner.In a series of elegant experiments the authors demonstrate that during cell differentiation, conventional chromatin architecture requires the sequential expression of first the NE transmembrane protein Lamin B receptor (LBR) and then its replacement by Lamin A/C, with some cell types expressing both proteins . The chrFigure 2A).Genome wide studies of LADs during neuronal differentiation in mice showed that while ESCs and terminally differentiated cells share a broad LAD structure, smaller sub regions of gene clusters undergo rearrangements corresponding to steps of the differentiation process . For exaDrosophila, the gene encoding a critical transcriptional factor hunchback was shown to move to the nuclear lamina during differentiation of neuroblast cells to neurons  repeats array, introduced into the genome of human culture cells, and the ability of the Lap2β-LacI to silence genes near its target site was similarly found to be dependent on HDAC activity.How do Lamins bind to heterochromatin or developmentally silenced genes? In addition to reports of a DNA binding domain in Lamin A  and in vhistones , there ahistones . The authistones . In thisOn a cautionary note, initial DamID studies of Lamin-chromatin binding sites required a population of cells, and thus the resulting LADs are reflections of both an average of many cells in a population as well as an amalgamation of binding events acquired over the time a DamID fusion protein is expressed. When these studies were repeated using the m6A-tracer technique which is able to label stochastic protein-Dam chromatin interactions in single, living cells, the authors found that at a given time only a subset of the initially described LADs was localized to the periphery while the rest were often located in the nuclear interior and further, this subset often changed following each cell division . Use of The nuclear envelope is a double lipid bilayer system made of the INM, directly adjacent and connected to the Lamin filaments, and the outer nuclear membrane (ONM), which is contiguous with the endoplasmic reticulum. The space between these membranes is called the perinuclear space (PNS) and is interrupted by NPCs which fenestrate the NM. Originally viewed as simply a protective barrier for the genome, the nuclear envelope along with its nuclear envelope transmembrane proteins (NETs) and associated soluble proteins are now known to participate in an array of cellular functions including genome organization, nuclear migration and positioning, cell cycle regulation, signaling, and cell differentiation . While tFigure 1). These tissue specific results were directly verified for several novel NETs by immunofluorescence staining and comparison with known tissue specific expression profiles . Secondly, these results suggest that NETs bind specific chromosomes in a reversible manner, linking chromosome positioning with differentiation . In this manner, tissue specific NETs may function to reposition entire chromosomes or large chromosomal regions to the nuclear periphery, which may further assist or stabilize the silencing of specific developmental genes by association with the nuclear lamina . Thirdly, multiple NETs can act to position the same chromosome, perhaps via cellular regulation of relative abundance of different NETs. Lastly, in addition to tissue specific expression levels, several of the NETs in this study appear to have tissue specific splice variants. Together these provide another layer of regulation to how a cell might fine-tune its gene expression profile during differentiation by utilizing NETs to position chromosomes at the NE in a tissue specificmanner.This study yields several important conceptual findings: firstly, it provides examples of tissue specific NET expression, giving rise to unique NE compositions correlating with cell type  experiments analyzing mobility of LBR truncation mutants revealed domains involved in interactions with histone H4, but not with Lamin B1 or B2 are required for formation of stable LBR microdomains in the NE. To investigate a role for LBR in heterochromatin formation, in vitro experiments using atomic force microscopy to measure chromatin compaction showed incubation of recombinant LBR with reconstituted chromatin resulted in highly aggregated chromatin fibers compared with controls. This study further demonstrated that LBR itself has the ability to repress transcription of a reporter plasmid.Lamin B receptor, discussed above, is an INM protein shown to interact directly with Lamin B and the chromodomain heterochromatic protein HP1 . Initialin vivo effects of LBR depletion or mutation  was first described .One can imagine a model where Nesprin isoforms are expressed in response to developmental signals and then themselves confer cytoskeletal changes as well as alter 3D organization of the genome to promote further tissue specific gene expression. They can do so via relaying these signals to INM proteins or through their own, yet undetermined, nucleoplasmic roles. Additionally, changes in nuclear size, shape and relative position within the cell can potentially influence the kinetics of nuclear processes and thus gene expression. Perhaps the most exciting implication of the LINC complex lies in its connection of the chromatin-associated INM proteins to cytoskeletal proteins via Nesprins, suggesting that cytoplasmic forces can directly move or alter nuclear chromatin positioning. This idea is supported by studies in both  bridges . The larThe NPCs are multi-component protein complexes that form selectively permeable channels through the NE. The primary function of the NPCs is to mediate nucleo-cytoplasmic transport of molecules and thus allow communication between the nucleus and the cytoplasm . They arVia its transport functions, the NPC plays an obvious role in gene regulation by controlling export of generated RNA and import of transcription and signaling factors. Yet, in addition to its canonical transport role, the NPC and individual Nups have been shown to play a role in genome organization and gene expression via direct binding to specific genomic locations . Multiplin situ RNA hybridization studies of the early Drosophila embryo revealed that Nups vary in their expression patterns relative to embryonic segments and developmental time points .Perhaps the most remarkable and well characterized example of a nuclear pore component playing a role in differentiation is that of Nup210. The transmembrane nucleoporin Nup210 is absent in mouse progenitor myoblasts and ESCs, but its expression is sharply upregulated during differentiation of these lineages into myotubes and neuroprogenitors, respectively . Nup210 Wnt signaling, a central developmental signaling pathway of multi-cellular organisms, has also been repeatedly linked to the nuclear pore . Wnt sigThese findings illustrate that Wnt pathway components are regulated by FG Nups both in terms of transport and function. Given the indispensable nature of Wnt signaling in stem cell maintenance, embryonic development and cell migration, these connections heavily implicate Nups in both normal development and oncogenic transformation. Intriguingly, the pluripotency state itself has been postulated to be regulated by the NPC via controlling levels of the pluripotency factors Oct4, Sox2 and Nanog in the nucleus . TogetheThe phenotypes of Nups in tissue specific differentiation, described above, can result from either the transport or the genome regulatory roles of Nups, or possibly, from the integration of both. Multiple examples of cell type specific transport have been reported, and proposed transport mechanisms of Nups in development have been reviewed recently . Here, wA functional relationship between nuclear pores and nuclear organization of chromatin was originally proposed based on EM close ups of mammalian nuclei that show frequent association of what appears to be decondensed chromatin with nuclear pores . Such liSaccharomyces cerevisiae demonstrated that some Nups, such as Mlp1, Nup2 and Nup60 often occupy regions of highly transcribed genes , such as tRNA and snoRNA genes, where they appear to be functionally required for correct RNA processing . In this manner, the NPC may represent a distinct nuclear environment that promotes a permissive chromatin state at the nuclear periphery, functionally opposed to the roles of the Lamins and NETs , but perhaps providing an accessible scaffold for switching between silenced and activated states during cell differentiation.Intriguingly and in line with their dynamic behavior,  nucleus . Both th nucleus . TogetheDrosophila Nup98 was found to associate with histone modifying complexes such as the histone methyl transferase Trithorax (Trx), the fly homolog of Mixed Lineage Leukemia (MLL), and the Non-Specific Lethal (NSL) Complex, which carries a conserved HAT males absent on the first . The earliest genome wide binding analysis of various Nups in yeast demonstrated that the stable yeast Nup84  binds to loci that are not enriched for transcriptional activity, and thus termed “neutral” chromatin , which bears direct relevance to the establishment of cell type specific gene expression programs. Whether the metazoan NPC primarily functions as a scaffold for expression of RNAP II and RNAP III genes, for establishment of chromatin boundaries or for additional regulation of silenced genes remains to be fully deciphered. It is possible that this large protein complex can accommodate interactions with all three types of loci via different Nups. Furthermore, the stable proteins of the NPC have been shown to be remarkably long-lived. Once assembled, the NPC core essentially does not turn over during the entire life span of post-mitotic cells, such as neurons  receptor signaling to maintain cyst stem cells and support differentiation of germ stem cells . Tissue specific expression of Lamin isotypes appears to be important for tethering heterochromatin to the nuclear periphery and for repositioning critical developmental genes to a silencing nuclear compartment . This role of nuclear lamina is closely linked to and likely executed through the functions of INM proteins, which have the ability to interact with chromatin bound regulators and histone modifying complexes. Expression of NETs has been shown to be highly cell type specific and likely drives the reorganization of chromosomes and large genomic regions needed for certain paths of differentiation . Finally, components of the NPC are functionally implicated in regulation of developmentally induced active genes and in setting up boundaries between chromatin domains . The composition of the NPC may vary depending on the cell type, with some Nups such as Nup210 being added to drive critical differentiation steps. Developmentally regulated genes and boundaries may thus be recruited to the NPC in a tissue specific manner, or recruit Nups to their intranuclear locations. An exciting new direction stemming from these models is how developmental signaling factors that enter the nucleus during differentiation of particular lineages may cofunction with NE proteins and influence their genomic binding.Accumulating evidence has demonstrated tissue specific presence and functions of various NE components. Much of that knowledge supports the model that many of these functions are carried out via cell type specific interactions between the NE and the genome, which contribute to the correct establishment of tissue specific gene expression (Together the presented data also illustrate the interconnected roles of nuclear compartments essential for cell fate determination, from the earliest steps of chromatin structure rearrangement to the last stages of morphological and other changes. Perhaps a more accurate view of the NE-genome interplay involves a myriad of overlapping mechanisms with increasing specificity during differentiation. The NE composition may be another “cellular code” for specifying tissue specific gene expression programs through its contacts with the underlying chromatin. Similarly to other highly complex regulatory networks, future applications of the systems biology view of this “code” may be particularly beneficial for fully understanding the role of the NE in genome function and cell fate.


Proliferating cells such as tumor cells have increased metabolic demands that include ATP, NADPH, lipids, proteins, and nucleotides to allow for a tumor cell to divide into two daughter cells . Tumor cToday, there is consensus that combination of gain of function of oncogenes, loss or tumor suppressor and aberrant activation of signaling pathways downstream of growth factor signaling induce the Warburg effect . This inIt is important to note that mitochondria are indeed functional in most tumor cells. However, there are a fraction of tumor cells that have been shown to exhibit mitochondrial dysfunction due to loss of function mutations in the TCA cycle enzymes succinate dehydrogenase (SDH) or fumarate hydratase (FH) . These cThe author declares that he has no competing interests.


Parasites comprise a substantial portion of total biodiversity. Ultimately, this means that host extinction could result in many secondary extinctions of obligate parasites and potentially alter host-parasite network structure. Here, we examined a highly resolved fish-parasite network to determine key hosts responsible for maintaining parasite diversity and network structure (quantified here as nestedness and modularity). We evaluated four possible host extinction orders and compared the resulting co-extinction dynamics to random extinction simulations; including host removal based on estimated extinction risk, parasite species richness and host level contributions to nestedness and modularity. We found that all extinction orders, except the one based on realistic extinction risk, resulted in faster declines in parasite diversity and network structure relative to random biodiversity loss. Further, we determined species-level contributions to network structure were best predicted by parasite species richness and host family. Taken together, we demonstrate that a small proportion of hosts contribute substantially to network structure and that removal of these hosts results in rapid declines in parasite diversity and network structure. As network stability can potentially be inferred through measures of network structure, our findings may provide insight into species traits that confer stability. Species extinctions can alter community dynamics2343Despite the potential importance of host species identity, traits, and interaction patterns to secondary extinction dynamics810312Network structure is commonly quantified using topological network measures to describe the tendency for interactions in a network to be organized in a particular manner. These metrics describing network structure have often been related to measures of network stability, such as structural stability1415161718162021Currently, co-extinction studies tend to measure the effects of an extinction event on the diversity of the network2339C = 0.022), similar to other fish-parasite networks27et al. (2012)The current study utilizes data from a Long Term Ecological Research study on the fish and parasite communities of the Upper Paraná River floodplain, a 230 km long dam-free portion of the Paraná River in southern Brazil. Fish were sampled quarterly for eight years (2000–2008) by using both active and passive sampling techniques, resulting in a total of 4,875 fish captures of 72 species selected for parasitological analysis, Native species (n = 49) outnumbered non-native species (n = 23) of those fish species chosen for parasitological analyses. Parasites n = 324) were identified to the best possible resolution, which resulted in 140 parasites identified to the species level, 120 to genus, and 64 to family were idewww.FishBase.org, accessed 08/2014] a comprehensive fish life history trait database accessible in R using rfishbaseet al. (2012)a priori reason to exclude data, and our analysis method was insensitive to issues of collinearity and overparameterization. Parasite species richness was quantified as the number of parasite species found on a given host species. Measures obtained from FishBase included host extinction risk (“vulnerability”)et al. (2004)50, represents the expected loss in phylogenetic diversity under species extinction, assuming that all other species have equiprobable extinction risk. Measure of sampling effort, fish abundance, and biomass were obtained from Lima et al. 2012et al. (2012)et al. (2009)Data on fish traits  were obti), a measure of the importance of a single node to overall network structure, was calculated following Saavedra (2011)i) was calculated in the same way, but using Barber’s Q statistici or Qi close to zero indicate little or null impact of that host on network structure, while positive (negative) values are indicative of hosts that enhance (reduce) nestedness or modularity.We quantified nestedness using a metric based on overlap and decreasing matrix fill (NODF)Saavedra 11i) was a) each interaction equiprobable b) probability of interaction determined by parasite host breadth and c) probability of interaction determined by average of host and parasite occurrence probabilities (b from above), and relationships between measures obtained from the different null models are presented as supplementary material , we used regression tree analysis. Regression trees are a useful tool for the identification of the most important predictor variables, and have been used extensively in ecological applications353637In order to assess the potential relationship between host traits and their corresponding contributions to network structure In order to assess the impact of host extinction on network structure and parasite diversity, we sequentially removed hosts according to four potential extinction orders. We removed hosts from the network in order from highest to lowest host extinction risk (as estimated by Cheung DA) between the curve generated from a targeted extinction scenario and the mean curve generated from random extinction simulations in terms of parasite diversity (DAPSR), nestedness (DAC), and modularity (DAQ). This measure is almost identical to how Evans et al. (2013)After each host removal, nestedness (NODF), modularity (Q), and parasite diversity  were determined. Hosts were removed in random order for 1000 simulations to provide appropriate bounds of expected trajectories for the decay of nestedness, modularity, and parasite diversity. To measure the magnitude of the effect of each of the four species removal scenarios, we compared the decay curves of our targeted removal scenarios to a null expectation generated by 1000 random extinction simulations. From these simulations, we quantified the divergence of our targeted extinction scenarios to random simulations. To do this, we first plotted the decay in parasite diversity, modularity, or nestedness as a function of the number of hosts removed for each of our targeted and random simulations. Then we quantified the decay area . Fish host traits were obtained from FishBase (Froese and Pauly 2012) and from Agostinho et al. (2004).Host-parasite interaction matrices are provided in the supplementary material of Lima s = 0.485, p-value < 0.0001).Hosts contributed differentially to network properties, resulting in many hosts having a negligible effect on nestedness or modularity, while a small number of hosts had large positive effects on network structure measures. Contrary to the idea that modularity and nestedness have opposing influences on network structure (i.e. should be negatively correlated), we found a significant positive relationship between the two measures (ri and Qi), suggesting the importance of biomass to Ci could relate more to host biology and community composition than sampling effort.Host-specific contributions to nestedness and modularity were most associated with parasite species richness based on the relative contribution (RC) values obtained from the boosted regression tree analysis . Host faDA) in parasite diversity(DAPSR), nestedness (DAC), and modularity (DAQ)   and 3 coty (DAQ) .Host removal based on parasite species richness values resulted in larger decay area values than removal of hosts based on their estimated nestedness and modularity contribution , suggestAnother interesting result is what happens to modularity values with any (random or non-random) host removal. Modularity values actually increase until a critical point, after which they go to zero. This is likely a result of the modularity calculation itself. We demonstrate this in the Supplementary Materials  by numerThere are many host removal strategies not examined here. For instance, host extinction may be related to their native or non-native status, or their abundance within the community. While these analyses may be outside of the scope of the current manuscript, we have examined both in the Supplementary Materials  statistic can be considered a measure of network robustnessPrevious studies have argued that topological measures of network structure may confer stability1489Anostomidae  had the highest positive values of Ci and Qi and also the highest parasite species richness relative to other fish taxa. While the importance of host family may be conflated with parasite species richness, it is also possible that host family represents a coarse measure of phylogenetic relatedness, such that host family can be considered a proxy for evolutionary relatedness. Alternatively, this could simply be a variable related to unmeasured trait variation. Rank correlations between extinction scenarios show support for the relationship between species contributions to network structure and parasite species richness . Overall, this suggests that parasite species richness may be the most important determinant of network structure and parasite diversity, even when compared to metrics that calculate species-level contributions to nestedness and modularity. There are a number of possible explanations for this.While the importance of host family to species level contributions to nestedness and modularity could be viewed in an evolutionary context, it is potentially a result of the variation in parasite species richness seen in the fish taxa examined. For example, the family First, nestedness and modularity contribution metrics were not dynamically updated as species were removed. This was intentional, as the goal of this study was to determine if a snapshot of a full network could capture node importance as the network disassembles. This result makes intuitive sense, as the removal of host species with species-rich parasite communities may be more likely to result in co-extinction of parasite species. This finding, despite its appealing simplicity may not be true for some networks, as other aspects of network structure, host biology and community dynamics may also be important for network stabilityThrough simulated sequential host extinctions, we found that parasite diversity declined at a slightly faster rate when extinction order was based on host extinction risk than compared to random extinction order, but only after around 40% of hosts were already lost from the system. This suggests that the loss of host biodiversity based on realistic estimates of extinction risk may result in a greater loss of parasite diversity through secondary extinctions than is currently expected, but only in highly perturbed systems subject to large losses in host diversity. This result is comparable to Davies and Yessoufou (2013)While parasite diversity and nestedness declined precipitously in our simulations, modularity actually increased slowly in our extinction scenarios relative to random extinction simulations. This finding may be a function of removing hosts with high parasite species richness as this may fragment the network into small groups of specialist parasites, which would increase modularity. In a limiting case, a host-parasite network in which each host is parasitized by a single host-specific parasite would be perfectly modular. However, modularity increased even in random extinction simulations, suggesting one of two things; either modularity statistics are biased by matrix size or host removal from a network may actually increase modularity until a critical point is reached before the network collapses entirely. We address the relationship between matrix size and modularity in the Supplementary Materials .Biodiversity loss is a pressing concern, with recent focus on the impact of host extinctions on secondary extinctions of obligate parasites47How to cite this article: Dallas, T. and Cornelius, E. Co-extinction in a host-parasite network: identifying key hosts for network stability. Sci. Rep. 5, 13185; doi: 10.1038/srep13185 (2015).


Traumatic brain injury (TBI) is a heterogeneous disorder with many factors contributing to a spectrum of severity, leading to cognitive dysfunction that may last for many years after injury. Injury to axons in the white matter, which are preferentially vulnerable to biomechanical forces, is prevalent in many TBIs. Unlike focal injury to a discrete brain region, axonal injury is fundamentally an injury to the substrate by which networks of the brain communicate with one another. The brain is envisioned as a series of dynamic, interconnected networks that communicate via long axonal conduits termed the “connectome”. Ensembles of neurons communicate via these pathways and encode information within and between brain regions in ways that are timing dependent. Our central hypothesis is that traumatic injury to axons may disrupt the exquisite timing of neuronal communication within and between brain networks, and that this may underlie aspects of post-TBI cognitive dysfunction. With a better understanding of how highly interconnected networks of neurons communicate with one another in important cognitive regions such as the limbic system, and how disruption of this communication occurs during injury, we can identify new therapeutic targets to restore lost function. This requires the tools of systems neuroscience, including electrophysiological analysis of ensemble neuronal activity and circuitry changes in awake animals after TBI, as well as computational modeling of the effects of TBI on these networks. As more is revealed about how inter-regional neuronal interactions are disrupted, treatments directly targeting these dysfunctional pathways using neuromodulation can be developed. Traumatic brain injury (TBI) can disrupt cognitive processing and memory function for many years post injury , and to the function of regional and global neural networks .ex vivo brain slice preparations from rodent TBI models, or in vitro neuron culture preparations that have been mechanically injured. Axonal injury can lead to secondary changes in the channels, ionic homeostasis and myelination necessary for timely and robust action potential propagation. In vitro models have demonstrated that there is substantial ionic disruption at lower levels of axonal strain  is used to determine global or regional brain network differences between human TBI patients and healthy controls, which are then correlated to cognitive dysfunction. Structural imaging techniques such as DTI can delineate broadly the white matter patterns of injury and attempt to link them to both cognitive dysfunction (see above) as well as network abnormalities determined by fMRI  as well as the local and global breakdown of interactions between ensembles?How does this network dysfunction lead to memory and executive function impairment seen after TBI?within the theta frequency range, but not outside of it, has been shown to recover behavior in these models  and temporal (over time) representations of the above examples  coordinated over such long distances? How is it that ensembles in the cortex receive discrete contextual information from groups of cells in the hippocampus such as “place” cells? One mechanism for coordinating different regions of the brain and transmitting information between them is an oscillation, a foundational concept in neuroscience and neurology whose mechanistic role in these processes has been debated since its discovery. Another concept for distributed representations of information in the cortex are “syn-fire chains”, a model that demonstrated that a synchronously firing series of neurons could propagate (or transmit) information through noisy layers  to be more synchronous with the dominant currents it is receiving. A single neuron has many sources of current, both excitatory (depolarizing) and inhibitory (hyperpolarizing) from many local and distant brain regions that are integrated over time. One can envision that if one or more afferent white matter tracts have been injured, the inflow of synaptic currents to a given neuronal ensemble may no longer be sufficiently coordinated to maintain its precisely timed output, leading to functional impairment.local field potential (LFP). Cortical LFP can be measured with scalp EEG, subdural electrode grids, or with individual electrodes placed in the brain. The LFP of deeper structures  requires depth electrodes that penetrate the structure. Patterns of oscillations in the LFP within different frequency bands have been observed in all mammalian species studied and are linked to behavioral states , is a well described phenomenon whereby neurons that fire reinforce the synapses on their own dendrites using back-propagating actions potentials . Further, much is known about the role of oscillatory activity and precision timing within hippocampal networks as they relate to memory formation, consolidation and executive function.In the awake animal, two dominant electrophysiological states have been described in the hippocampus. In the rodent, theta frequency band oscillations (approximately 4–10 Hz) dominate the hippocampal LFP during spatial exploratory activity, memory tasks, and REM sleep Buzsáki, . ImmobilPerhaps the most well-studied neuronal function to date is that of the hippocampal place cell. First described in rats by O’Keefe and Dostrovsky , place cAlthough the mechanisms are poorly understood, it is clear that the formation of a place cell is dependent on coordinated input into the hippocampus from “grid cells” found in the entorhinal cortex, via direct and indirect projections to the CA1 hippocampal subfield along the perforant and temporoammonic pathways. Lesions to the direct projections from entorhinal cortex to CA1 result in impaired place cell formation  and has recently received a great deal of attention  fire in temporal sequence entrained to the theta oscillation (see above), but each individual ensemble is locked to a cycle of the gamma oscillation. Several gamma cycles are, in turn, phase-locked to a single theta cycle. In this way gamma oscillations serve to organize neuronal ensembles representing individual memory items, while the phase relationship to theta oscillations serves to organize these memory items into a defined temporal sequence, forming the basis of episodic memory and potentially serving as the structure that allows distribution across brain regions  state of the hippocampus is thought to be internally generated, dominant during quiet rest, eating, grooming, and deep, non-REM sleep Buzsáki, . Indeed,The functional significance of the hippocampal SPW-R state is not well-understood, but there is increasing evidence that it may play a critical role in memory consolidation and re-distribution to extra-hippocampal brain regions  neurons to hippocampal theta  leads to timing delays in neuronal communication particularly relevant to TBI symptoms. Several overarching hypotheses emerge:TBI induced axonal injury results in loss of, or derangement in synchronization within intra-hippocampal connections. This may affect proper hippocampal oscillatory function, including the temporal organization of neuronal ensembles involved in memory construction .TBI induced axonal injury results in loss of, or pathological delay in synaptic input into the hippocampus. This may affect organizing oscillations from extra-hippocampal sources , proper formation of neuronal ensembles encoding spatial or episodic memories, and the coordination of both.TBI induced axonal injury to long-range connections between the hippocampus and other distant structures may impair coordinated oscillatory activity between these regions and adversely affect executive functions such as working memory, or affective processes such as fear conditioning.Neuromodulation strategies arising from these hypotheses would not only reveal anatomical targets for stimulation or inhibition, but also suggest timing frequency parameters for such interventions. For example, much of the history of deep brain stimulation for movement and psychiatric disorders, a classic neuromodulation therapy, has focused on anatomical targets and has largely employed an empirical method for determining stimulation parameters , the CURE Taking Flight Award, and the Codman Neurotrauma Award.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Platinum derivatives used as chemotherapeutic drugs such as cisplatin and oxaliplatin have a potent antitumor activity. However, severe side effects such as nephro-, oto-, and neurotoxicity are associated with their use. Effects and side effects of platinum-based drugs are in part caused by their transporter-mediated uptake in target and non target cells. In this mini review, the transport systems involved in cellular handling of platinum derivatives are illustrated, focusing on transporters for cisplatin. The copper transporter 1 seems to be of particular importance for cisplatin uptake in tumor cells, while the organic cation transporter (OCT) 2, due to its specific organ distribution, may play a major role in the development of undesired cisplatin side effects. In polarized cells, e.g., in renal proximal tubule cells, apically expressed transporters, such as multidrug and toxin extrusion protein 1, mediate secretion of cisplatin and in this way contribute to the control of its toxic effects. Specific inhibition of cisplatin uptake transporters such as the OCTs may be an attractive therapeutic option to reduce its toxicity, without impairing its antitumor efficacy. In order to reach sufficiently high concentrations, intracellular active drugs must cross the plasma membrane to reach their targets. This process, especially in the case of hydrophilic drugs, is mediated by specialized plasma membrane proteins called transporters. It is well known that efflux transporters are involved in the development of drug resistance    is a membrane protein that plays a significant role in the cellular cisplatin uptake  is a copper transport protein with substantial structural homology to Ctr1. Ctr2 is mainly expressed in late endosomes and lysosomes  and in Wilson's disease (inactivation of ATP7B), is associated with copper deficiency because of impaired copper efflux from enterocytes into the blood or massive cellular copper overload, respectively  808 G/T  with a protection against cisplatin nephrotoxicity  or a trans-membrane ion flux (secondary active), the plasma membrane potential creates both an electrical and a concentration gradient for their cationic substrates. This allows an accumulation of platinum derivatives in the cells to intracellular concentrations exceeding the extracellular level  for oxaliplatin transport. These transporters are expressed on the apical membrane of renal proximal tubule cells (Ciarimboli, In conclusion, cellular transport of platinum derivatives is mediated by several transport systems. Some transporters, such as OCTs, are specifically expressed in organs, which are damaged by antitumor therapy with platinum derivatives. For this reason, they may be a target for protective intervention. However, an efficient protection can be only reached by specific inhibition of OCTs.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.