Genes Confer Similar Robustness to Environmental,Stochastic, and Genetic Perturbations in Yeast

Gene inactivation often has little or no apparent consequence for the phenotype of an organism. This property—enetic (or mutational) robustness—is pervasive, and has important implications for disease and evolution, but is not well understood. Dating back to at least Waddington, it has been suggested that mutational robustness may be related to the requirement to withstand environmental or stochastic perturbations. Here I show that global quantitative data from yeast are largely consistent with this idea. Considering the effects of mutations in all nonessential genes shows that genes that confer robustness to environmental or stochastic change also buffer the effects of genetic change, and with similar efficacy. This means that selection during evolution for environmental or stochastic robustness (also referred to as canalization) may frequently have the side effect of increasing genetic robustness. A dynamic environment may therefore promote the evolution of phenotypic complexity. It also means that “hub” genes in genetic interaction (synthetic lethal) networks are generally genes that confer environmental resilience and phenotypic stability.     

Environmental Noise,Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions.     

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

Background

Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity.

Methodology

We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis.

Conclusions

F_ST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation.     

Robustness under Functional Constraint: The Genetic Network for Temporal Expression in Drosophila Neurogenesis

Precise temporal coordination of gene expression is crucial for many developmental processes. One central question in developmental biology is how such coordinated expression patterns are robustly controlled. During embryonic development of the Drosophila central nervous system, neural stem cells called neuroblasts express a group of genes in a definite order, which leads to the diversity of cell types. We produced all possible regulatory networks of these genes and examined their expression dynamics numerically. From the analysis, we identified requisite regulations and predicted an unknown factor to reproduce known expression profiles caused by loss-of-function or overexpression of the genes in vivo, as well as in the wild type. Following this, we evaluated the stability of the actual Drosophila network for sequential expression. This network shows the highest robustness against parameter variations and gene expression fluctuations among the possible networks that reproduce the expression profiles. We propose a regulatory module composed of three types of regulations that is responsible for precise sequential expression. This study suggests that the Drosophila network for sequential expression has evolved to generate the robust temporal expression for neuronal specification.     

Limits and Trade-Offs of Topological Network Robustness

We investigate the trade-off between the robustness against random and targeted removal of nodes from a network. To this end we utilize the stochastic block model to study ensembles of infinitely large networks with arbitrary large-scale structures. We present results from numerical two-objective optimization simulations for networks with various fixed mean degree and number of blocks. The results provide strong evidence that three different blocks are sufficient to realize the best trade-off between the two measures of robustness, i.e. to obtain the complete front of Pareto-optimal networks. For all values of the mean degree, a characteristic three block structure emerges over large parts of the Pareto-optimal front. This structure can be often characterized as a core-periphery structure, composed of a group of core nodes with high degree connected among themselves and to a periphery of low-degree nodes, in addition to a third group of nodes which is disconnected from the periphery, and weakly connected to the core. Only at both extremes of the Pareto-optimal front, corresponding to maximal robustness against random and targeted node removal, a two-block core-periphery structure or a one-block fully random network are found, respectively.     

Cloning of Choriocarcinoma Cells Shows That Invasion Correlates with Expression and Activation of Gelatinase A

Implantation and placental development are dependent upon trophoblast invasion of the endometrium. While the villous trophoblast does not display invasive behavior, the extravillous cytotrophoblast is highly invasive. By cloning BeWo choriocarcinoma cells, we have isolated two distinct clones that share similarities with villous and extravillous cytotrophoblasts. When cultured at the surface of a type I collagen gel, BeWo MC-1 cells were not invasive, whereas BeWo MC-2 cells rapidly invaded this matrix. When injected subcutaneously in nude mice, BeWo MC-1 cells developed a localized tumor and BeWo MC-2 cells developed larger tumors with micrometastases. Gelatinase A expression and minute amounts of gelatinase B were detected in the parental cell line and in both clones. However, the parental and the BeWo MC-2 cells secreted 5- to 10-fold more gelatinase A than the BeWo MC-1 cells. Laminin and matrigel stimulated the production of gelatinase A in BeWo MC-2 cells. Type I collagen promoted the conversion of the 72-kDa progelatinase A in an active enzyme only in parental BeWo and in BeWo MC-2 cells. These clones provide an interesting model for studying the complex mechanisms regulating implantation as well as the controlled invasiveness during implantation compared to tumor invasion.     

Robustness and Evolvability of the Human Signaling Network

Biological systems are known to be both robust and evolvable to internal and external perturbations, but what causes these apparently contradictory properties? We used Boolean network modeling and attractor landscape analysis to investigate the evolvability and robustness of the human signaling network. Our results show that the human signaling network can be divided into an evolvable core where perturbations change the attractor landscape in state space, and a robust neighbor where perturbations have no effect on the attractor landscape. Using chemical inhibition and overexpression of nodes, we validated that perturbations affect the evolvable core more strongly than the robust neighbor. We also found that the evolvable core has a distinct network structure, which is enriched in feedback loops, and features a higher degree of scale-freeness and longer path lengths connecting the nodes. In addition, the genes with high evolvability scores are associated with evolvability-related properties such as rapid evolvability, low species broadness, and immunity whereas the genes with high robustness scores are associated with robustness-related properties such as slow evolvability, high species broadness, and oncogenes. Intriguingly, US Food and Drug Administration-approved drug targets have high evolvability scores whereas experimental drug targets have high robustness scores.     

Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species

The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species to endure genetic perturbations. Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species'' lifestyle (specialized/generalist); the second, environmental-independent, is associated (correlation = ∼0.6) with the intrinsic metabolic capacities of a species—higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets.     

Specificity and Robustness of the Mammalian MAPK-IEG Network

The mitogen-activated protein kinase cascade is a conserved signal transduction pathway found in organisms of complexity spanning from yeast to humans. In many mammalian tissue types, this pathway can correctly transduce signals from different extracellular messengers, leading to specific and often mutually exclusive cellular responses. The transduced signal is tuned by a complicated set of positive and negative feedback control mechanisms and fed into a downstream gene expression network. This network, based on the immediate early gene system, has two possible, mutually exclusive outcomes. Using a mathematical model, we study how different stimuli lead to different temporal signal structure. Further, we investigate how each of the feedback controls contributes to the overall specificity of the gene expression output, and hypothesize that the complicated nature of the mammalian mitogen-activated protein kinase pathway results in a system able to robustly identify and transduce the proper signal without investing in two completely separate signal cascades. Finally, we quantify the role of the RKIP protein in shaping the signal, and propose a novel mechanism of its involvement in cancer metastasis.     

A Genetic Analysis of Tetrahymena That Have Aborted Normal Development

Conjugating Tetrahymena can abort the sexual cycle before the production of progeny somatic (macro-) nuclei and return to vegetative growth. We have analyzed the germinal (micronuclear) genotypes of these cells in order to determine the stage at which they aborted conjugation. Our data demonstrate that nearly all of these cells attempt meiosis, but that very few reach the successful completion of cross-fertilization. The resulting micronuclear genotypes suggest that either germinal chromosomes or entire nuclei are lost during an unsuccessful attempt at meiosis or cross-fertilization. We conclude that the decision to develop progeny macronuclei is made during meiosis and is dependent on the completion of some step necessary for successful cross-fertilization.     

Architecture-Dependent Robustness and Bistability in a Class of Genetic Circuits

Understanding the relationship between genotype and phenotype is a challenge in systems biology. An interesting yet related issue is why a particular circuit topology is present in a cell when the same function can supposedly be obtained from an alternative architecture. Here we analyzed two topologically equivalent genetic circuits of coupled positive and negative feedback loops, named NAT and ALT circuits, respectively. The computational search for the oscillation volume of the entire biologically reasonable parameter region through large-scale random samplings shows that the NAT circuit exhibits a distinctly larger fraction of the oscillatory region than the ALT circuit. Such a global robustness difference between two circuits is supplemented by analyzing local robustness, including robustness to parameter perturbations and to molecular noise. In addition, detailed dynamical analysis shows that the molecular noise of both circuits can induce transient switching of the different mechanism between a stable steady state and a stable limit cycle. Our investigation on robustness and dynamics through examples provides insights into the relationship between network architecture and its function.     

A Review of Dietary and Environmental Correlates of Obesity with Emphasis on Developing Countries

The relationships between dietary and environmental factors and obesity are reviewed. Findings from selected population studies of diet and body weight are presented. In general, the results from population studies of diet and obesity have been inconsistent and marked with methodological weaknesses, especially the use of cross-sectional study design. Apart from the diet, several social and economic factors appear to be important correlates of obesity in the population. However, most studies have focused on the socioeconomic status as abroad, composite measure. The relationships between income, education, occupation, place of residence, and obesity are reviewed here, with emphasis on the developing countries. In many developing countries, the changing dietary pattern, along with rising life expectancy and changing socioeconomic environment, has contributed to the increasing problems of obesity and other diet-related chronic diseases that will have an enormous impact on the health and health care resource of these countries in the near future.     

Critical Cooperation Range to Improve Spatial Network Robustness

A robust worldwide air-transportation network (WAN) is one that minimizes the number of stranded passengers under a sequence of airport closures. Building on top of this realistic example, here we address how spatial network robustness can profit from cooperation between local actors. We swap a series of links within a certain distance, a cooperation range, while following typical constraints of spatially embedded networks. We find that the network robustness is only improved above a critical cooperation range. Such improvement can be described in the framework of a continuum transition, where the critical exponents depend on the spatial correlation of connected nodes. For the WAN we show that, except for Australia, all continental networks fall into the same universality class. Practical implications of this result are also discussed.     

Robustness of a Neural Network Model for Differencing

A neural network, originally proposed as a model for nuclei in the auditory brainstem, uses gradients of cell thresholds to reliably compute the difference of inputs over wide input ranges. The encoding of difference is linear even though the individual components of the network are finite, saturating, nonlinear devices highly dependent on input level. Theorems are proven that explain the linear dependence of network output on difference and that show the robustness of the network to perturbations of the threshold gradients. There is some evidence that the network exists in the neural tissue of the auditory brainstem.     

Environmental Factors That Control Microbial Perchlorate Reduction

As part of a study to elucidate the environmental parameters that control microbial perchlorate respiration, we investigated the reduction of perchlorate by the dissimilatory perchlorate reducer Dechlorosoma suillum under a diverse set of environmental conditions. Our results demonstrated that perchlorate reduction by D. suillum only occurred under anaerobic conditions in the presence of perchlorate and was dependent on the presence of molybdenum. Perchlorate reduction was dependent on the presence of the enzyme chlorite dismutase, which was induced during metabolism of perchlorate. Anaerobic conditions alone were not enough to induce expression of this enzyme. Dissolved oxygen concentrations less than 2 mg liter⁻¹ were enough to inhibit perchlorate reduction by D. suillum. Similarly to oxygen, nitrate also regulated chlorite dismutase expression and repressed perchlorate reduction by D. suillum. Perchlorate-grown cultures of D. suillum preferentially reduced nitrate in media with equimolar amounts of perchlorate and nitrate. In contrast, an extended (40 h) lag phase was observed if a similar nitrate-perchlorate medium was inoculated with a nitrate-grown culture. Perchlorate reduction commenced only when nitrate was completely removed in either of these experiments. In contrast to D. suillum, nitrate had no inhibitory effects on perchlorate reduction by the perchlorate reducer Dechloromonas agitata strain CKB. Nitrate was reduced to nitrite concomitant with perchlorate reduction to chloride. These studies demonstrate that microbial respiration of perchlorate is significantly affected by environmental conditions and perchlorate reduction is directly dependent on bioavailable molybdenum and the presence or absence of competing electron acceptors. A microbial treatment strategy can achieve and maintain perchlorate concentrations below the recommended regulatory level, but only in environments in which the variables described above can be controlled.     

Effects of Genetic and Environmental Factors on Trait Network Predictions From Quantitative Trait Locus Data

The use of high-throughput genomic techniques to map gene expression quantitative trait loci has spurred the development of path analysis approaches for predicting functional networks linking genes and natural trait variation. The goal of this study was to test whether potentially confounding factors, including effects of common environment and genes not included in path models, affect predictions of cause–effect relationships among traits generated by QTL path analyses. Structural equation modeling (SEM) was used to test simple QTL-trait networks under different regulatory scenarios involving direct and indirect effects. SEM identified the correct models under simple scenarios, but when common-environment effects were simulated in conjunction with direct QTL effects on traits, they were poorly distinguished from indirect effects, leading to false support for indirect models. Application of SEM to loblolly pine QTL data provided support for biologically plausible a priori hypotheses of QTL mechanisms affecting height and diameter growth. However, some biologically implausible models were also well supported. The results emphasize the need to include any available functional information, including predictions for genetic and environmental correlations, to develop plausible models if biologically useful trait network predictions are to be made.     

Temporal Patterns and Environmental Correlates of Macroinvertebrate Communities in Temporary Streams

Temporary streams are characterised by short periods of seasonal or annual stream flow after which streams contract into waterholes or pools of varying hydrological connectivity and permanence. Although these streams are widespread globally, temporal variability of their ecology is understudied, and understanding the processes that structure community composition in these systems is vital for predicting and managing the consequences of anthropogenic impacts. We used multivariate and univariate approaches to investigate temporal variability in macroinvertebrate compositional data from 13 years of sampling across multiple sites from autumn and spring, in South Australia, the driest state in the driest inhabited continent in the world. We examined the potential of land-use, geographic and environmental variables to predict the temporal variability in macroinvertebrate assemblages, and also identified indicator taxa, that is, those highly correlated with the most significantly associated physical variables. Temporal trajectories of macroinvertebrate communities varied within site in both seasons and across years. A combination of land-use, geographic and environmental variables accounted for 24% of the variation in community structure in autumn and 27% in spring. In autumn, community composition among sites were more closely clustered together relative to spring suggesting that communities were more similar in autumn than in spring. In both seasons, community structure was most strongly correlated with conductivity and latitude, and community structure was more associated with cover by agriculture than urban land-use. Maintaining temporary streams will require improved catchment management aimed at sustaining seasonal flows and critical refuge habitats, while also limiting the damaging effects from increased agriculture and urban developments.