Direct and indirect ecosystem effects of evolutionary adaptation in the Trinidadian guppy (Poecilia reticulata)

Ecological and evolutionary processes may interact on the same timescale, but we are just beginning to understand how. Several studies have examined the net effects of adaptive evolution on ecosystem properties. However, we do not know whether these effects are confined to direct interactions or whether they propagate further through indirect ecological pathways. Even less well understood is how the combination of direct and indirect ecological effects of the phenotype promotes or inhibits evolutionary change. We coupled mesocosm experiments and ecosystem modeling to evaluate the ecological effects of local adaptation in Trinidadian guppies (Poecilia reticulata). The experiments show that guppies adapted to life with and without predators alter the ecosystem directly through differences in diet. The ecosystem model reveals that the small total indirect effect of the phenotype observed in the experiments is likely a combination of several large indirect effects that act in opposing directions. The model further suggests that these indirect effects can reverse the direction of selection that direct effects alone exert back on phenotypic variation. We conclude that phenotypic divergence can have major effects deep in the web of indirect ecological interactions and that even small total indirect effects can radically change the dynamics of adaptation.     

Geographic range size and evolutionary age in birds

Together with patterns of speciation and extinction, post-speciation transformations in the range sizes of individual species determine the form of contemporary species range-size distributions. However, the methodological problems associated with tracking the dynamics of a species' range size over evolutionary time have precluded direct study of such range-size transformations, although indirect evidence has led to several models being proposed describing the form that they might take. Here, we use independently derived molecular data to estimate ages of species in six monophyletic groups of birds, and examine the relationship between species age and global geographic range size. We present strong evidence that avian range sizes are not static over evolutionary time. In addition, it seems that, with the regular exception of certain taxa (for example island endemics and some threatened species), range-size transformations are non-random in birds. In general, range sizes appear to expand relatively rapidly post speciation; subsequently; and perhaps more gradually, they then decline as species age. We discuss these results with reference to the various models of range-size dynamics that have been proposed.     

Somatic DNA recombination in the brain

Possible somatic DNA recombination in the brain has been investigated by attempting to capture direct or indirect evidence of it. Until recently, the biological significance of the DNA event, the genes is involved in the recombination, or even whether the event actually occurs in the brain has remained unclear. The DNA-rearranged locus-oriented approach and the recombination activity-oriented approach have mutually contributed to the elucidation of the biological features of extra-immune system somatic DNA recombination. There have been only 2 loci proposed for the candidate, one is a repetitive sequence and the other DNA recombination is nonrepetitive locus. This review states conventional concepts and discussions chronologically and finally to the newest aspects of DNA rearrangement in the brain.     

Neuroevolution and complexifying genetic architectures for memory and control tasks

The way genes are interpreted biases an artificial evolutionary system towards some phenotypes. When evolving artificial neural networks, methods using direct encoding have genes representing neurons and synapses, while methods employing artificial ontogeny interpret genomes as recipes for the construction of phenotypes. Here, a neuroevolution system (neuroevolution with ontogeny or NEON) is presented that can emulate a well-known neuroevolution method using direct encoding (neuroevolution of augmenting topologies or NEAT), and therefore, can solve the same kinds of tasks. Performance on challenging control and memory benchmark tasks is reported. However, the encoding used by NEON is indirect, and it is shown how characteristics of artificial ontogeny can be introduced incrementally in different phases of evolutionary search.     

Development and validation of evolutionary algorithm software as an optimization tool for biological and environmental applications

A flexible, extendable tool for the optimization of (micro)biological processes and protocols using evolutionary algorithms was developed. It has been tested using three different theoretical optimization problems: 2 two-dimensional problems, one with three maxima and one with five maxima and a river autopurification optimization problem with boundary conditions. For each problem, different evolutionary parameter settings were used for the optimization. For each combination of evolutionary parameters, 15 generations were run 20 times. It has been shown that in all cases, the evolutionary algorithm gave rise to valuable results. Generally, the algorithms were able to detect the more stable sub-maximum even if there existed less stable maxima. The latter is, from a practical point of view, generally more desired. The most important factors influencing the convergence process were the parameter value randomization rate and distribution. The developed software, described in this work, is available for free.     

Simulated Evolutionary Optimization and Local Search: Introduction and Application to Tree Search

Tree search and its more complicated variant, tree search and simultaneous multiple DNA sequence alignment, are difficult NP-complete optimization problems, which require the application of advanced computational techniques, if large data sets are to be solved within reasonable computation times. Traditionally tree search has been attacked with a search strategy that is best described as multistart hill-climbing; local search by branch swapping has been performed on several different starting trees. Recently a different tree search strategy was tested in the Parsigal parsimony program, which used a combination of evolutionary optimization and local search. Evolutionary optimization algorithms use principles adopted from biological evolution to solve technical optimization tasks. Evolutionary optimization is a stochastic global search method, which means that the method is able to escape local optima, and is in principle able to produce any solution in the search space (although this may take a long time). Local search techniques, such as branch swapping, employ a completely different search strategy; they exploit local information maximally in order to achieve quick improvement in the value of the objective function. However, local search algorithms lack the ability to escape from local optima, which is a fundamental requirement for any search algorithm that aims to be able to discover the global optimum of a multimodal optimization problem. Hence it seems that an optimization strategy combining the good properties of both evolutionary algorithms and local search would be ideal. In this study, aspects of global optimization and local search are discussed, and the method of simulated evolutionary optimization is reviewed in detail. The application of simulated evolutionary optimization to tree search in Parsigal is then reviewed briefly.     

Identification of Important Nodes in Directed Biological Networks: A Network Motif Approach

Identification of important nodes in complex networks has attracted an increasing attention over the last decade. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness and PageRank. Different measures consider different aspects of complex networks. Although there are numerous results reported on undirected complex networks, few results have been reported on directed biological networks. Based on network motifs and principal component analysis (PCA), this paper aims at introducing a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks, such as finding command interneurons, global regulators and non-hub but evolutionary conserved actually important nodes in biological networks. Receiver Operating Characteristic (ROC) curves for the five networks indicate remarkable prediction accuracy of the proposed measure. The proposed index provides an alternative complex network metric. Potential implications of the related investigations include identifying network control and regulation targets, biological networks modeling and analysis, as well as networked medicine.     

Pairwise alignment of protein interaction networks.

With an ever-increasing amount of available data on protein-protein interaction (PPI) networks and research revealing that these networks evolve at a modular level, discovery of conserved patterns in these networks becomes an important problem. Although available data on protein-protein interactions is currently limited, recently developed algorithms have been shown to convey novel biological insights through employment of elegant mathematical models. The main challenge in aligning PPI networks is to define a graph theoretical measure of similarity between graph structures that captures underlying biological phenomena accurately. In this respect, modeling of conservation and divergence of interactions, as well as the interpretation of resulting alignments, are important design parameters. In this paper, we develop a framework for comprehensive alignment of PPI networks, which is inspired by duplication/divergence models that focus on understanding the evolution of protein interactions. We propose a mathematical model that extends the concepts of match, mismatch, and gap in sequence alignment to that of match, mismatch, and duplication in network alignment and evaluates similarity between graph structures through a scoring function that accounts for evolutionary events. By relying on evolutionary models, the proposed framework facilitates interpretation of resulting alignments in terms of not only conservation but also divergence of modularity in PPI networks. Furthermore, as in the case of sequence alignment, our model allows flexibility in adjusting parameters to quantify underlying evolutionary relationships. Based on the proposed model, we formulate PPI network alignment as an optimization problem and present fast algorithms to solve this problem. Detailed experimental results from an implementation of the proposed framework show that our algorithm is able to discover conserved interaction patterns very effectively, in terms of both accuracies and computational cost.     

There must be a prokaryote somewhere: microbiology''s search for itself.

While early microbiologists showed considerable interest in the problem of the natural (evolutionary) relationships among prokaryotes, by the middle of this century that problem had largely been discarded as being unsolvable. In other words, the science of microbiology developed without an evolutionary framework, the lack of which kept it a weak discipline, defined largely by external forces. Modern technology has allowed microbiology finally to develop the needed evolutionary framework, and with this comes a sense of coherence, a sense of identity. Not only is this development radically changing microbiology itself, but also it will change microbiology's relationship to the other biological disciplines. Microbiology of the future will become the primary biological science, the base upon which our future understanding of the living world rests, and the font from which new understanding of it flows.     

Parenting Strategies in Modern and Emerging Economies

Independent of ecology, subsistence strategy, social complexity, or other aspects of socioecology, the altricial nature of young humans requires mothers to have help raising their offspring. What seems to be context-dependent, however, is who the helpers are, how they invest, and what the impacts of that investment are. In a series of papers that focus on parental and alloparental investment across five populations, this special issue of Human Nature uses evolutionary theory to examine how socioecological context influences modes of direct parental investment among the boat-dwelling Shodagor of Bangladesh (Starkweather), modes of indirect paternal investment in the modern United States (Anderson), and the biological outcome of paternal investment for men in Jamaica (Gray et al.), as well as direct alloparental investment among village Bangladeshis (Perry) and indirect alloparental investment in breastfeeding practices in the United States (Cisco).     

There must be a prokaryote somewhere: microbiology's search for itself.

While early microbiologists showed considerable interest in the problem of the natural (evolutionary) relationships among prokaryotes, by the middle of this century that problem had largely been discarded as being unsolvable. In other words, the science of microbiology developed without an evolutionary framework, the lack of which kept it a weak discipline, defined largely by external forces. Modern technology has allowed microbiology finally to develop the needed evolutionary framework, and with this comes a sense of coherence, a sense of identity. Not only is this development radically changing microbiology itself, but also it will change microbiology''s relationship to the other biological disciplines. Microbiology of the future will become the primary biological science, the base upon which our future understanding of the living world rests, and the font from which new understanding of it flows.     

A discussion of the chemistry of oxidative and nitrosative stress in cytotoxicity

Nitric oxide (NO) has been shown to be a key bioregulatory agent in a wide variety of biological processes, yet cytotoxic properties have been reported as well. This dichotomy has raised the question of how this potentially toxic species can be involved in so many fundamental physiological processes. We have investigated the effects of NO on a variety of toxic agents and correlated how its chemistry might pertain to the observed biology. The results generate a scheme termed the chemical biology of NO in which the pertinent reactions can be categorized into direct and indirect effects. The former involves the direct reaction of NO with its biological targets generally at low fluxes of NO. Indirect effects are reactions mediated by reactive nitrogen oxide species, such as those generated from the NO/O2 and NO/O2- reactions, which can lead to cellular damage via nitrosation or oxidation of biological components. This report discusses several examples of cytotoxicity involved with these stresses.     

Insulin resistance in type 2 diabetes -- role of the adipokines

The role of adipocytes as protein secreting cells has been known for almost 15 years. Most of these proteins have known biological activity and are called adipokines. However, only a few of the adipokines have been shown to regulate insulin sensitivity. The latter effects are direct or indirect. The adipokines regulating insulin sensitivity are tumor necrosis factor alpha, adiponectin, interleukin-6, resistin and leptin. This review examines the mechanism how these adipokines influence insulin sensitivity, how the adipocyte production of the adipokines is regulated and if genetic variance in the genes encoding for adipokines is important for the development of type 2 diabetes mellitus.     

Indirect genetic effects from ecological interactions in Arabidopsis thaliana

Indirect genetic effects arise when genes expressed in one individual affect the expression of traits in other individuals. The importance of indirect genetic effects has been recognized for a diversity of evolutionary processes including kin selection, sexual selection, community structure and multilevel selection, but data regarding their genetic architecture and prevalence throughout the genome remain scarce, especially for interactions between unrelated individuals. Using a set of 411 Bay-0 x Shahdara Arabidopsis recombinant inbred lines grown with Landsberg neighbours, we examined quantitative trait loci (QTL) having direct and indirect effects on size, developmental, and fitness related traits. Using an interval mapping approach, we identified 15 QTL with direct effects and found that 13 of these QTL had significant indirect effects on trait expression in neighbouring plants. These results suggest widespread pleiotropy, as nearly all direct effect QTL have associated pleiotropic indirect effects. Paradoxically, most indirect effects were of the same sign as direct effects, creating a pattern of nearly universal positive pleiotropy that makes most covariances between direct and indirect effects positive. These results are consistent with a complex genetic basis for intraspecific interactions, but suggest that interactions between neighbouring plants are largely positive, rather than negative as would be expected for competition. In addition to their evolutionary and ecological importance, these pleiotropic relationships between DGE and IGE loci have implications for quantitative genetic studies of natural populations as well as experimental design considerations. Additionally, studies that ignore IGEs may over- or underestimate quantitative genetic parameters, as well as the effect of and variance contributed by QTL.     

微藻光生物水解制氢技术

氢气是未来人类社会可持续发展的理想能源。介绍微藻太阳能光生物水解制氢的研究现状,重点讨论微藻光水解制氢的生物学原理。重点讨论微藻光解水制氢的酶学机理、工艺过程以及当前的主要研究方向。通过比较微藻固氮酶制氢、可逆产氢酶直接光水解制氢、可逆产氢酶间接光水解制氢等技术路线的优缺点,指出利用微藻可逆产氢酶两步法间接光水解制氢最具发展潜力,可望为21世纪的“氢能经济社会”提供大量的氢源。该技术成功的关键在于相关的基因工程和代谢调控研究取得重大突破。