A complex adaptive systems approach to the kinetic folding of RNA

The kinetic folding of RNA sequences into secondary structures is modeled as a complex adaptive system, the components of which are possible RNA structural rearrangements (SRs) and their associated bases and base pairs. RNA bases and base pairs engage in local stacking interactions that determine the probabilities (or fitnesses) of possible SRs. Meanwhile, selection operates at the level of SRs; an autonomous stochastic process periodically (i.e., from one time step to another) selects a subset of possible SRs for realization based on the fitnesses of the SRs. Using examples based on selected natural and synthetic RNAs, the model is shown to reproduce characteristic (nonlinear) RNA folding dynamics such as the attainment by RNAs of alternative stable states. Possible applications of the model to the analysis of properties of fitness landscapes, and of the RNA sequence-to-structure mapping are discussed.     

Conceptualizing microbe–plasmid communities as complex adaptive systems

Plasmids shape microbial communities’ diversity, structure, and function. Nevertheless, we lack a mechanistic understanding of how community structure and dynamics emerge from local microbe–plasmid interactions and coevolution. Addressing this gap is challenging because multiple processes operate simultaneously at multiple levels of organization. For example, immunity operates between a plasmid and a cell, but incompatibility mechanisms regulate coexistence between plasmids. Conceptualizing microbe–plasmid communities as complex adaptive systems is a promising approach to overcoming these challenges. I illustrate how agent-based evolutionary modeling, extended by network analysis, can be used to quantify the relative importance of local processes governing community dynamics. These theoretical developments can advance our understanding of plasmid ecology and evolution, especially when combined with empirical data.     

Molecular basis of adaptive convergence in experimental populations of RNA viruses

Characterizing the molecular basis of adaptation is one of the most important goals in modern evolutionary genetics. Here, we report a full-genome sequence analysis of 21 independent populations of vesicular stomatitis ribovirus evolved on the same cell type but under different demographic regimes. Each demographic regime differed in the effective viral population size. Evolutionary convergences are widespread both at synonymous and nonsynonymous replacements as well as in an intergenic region. We also found evidence for epistasis among sites of the same and different loci. We explain convergences as the consequence of four factors: (1) environmental homogeneity that supposes an identical challenge for each population, (2) structural constraints within the genome, (3) epistatic interactions among sites that create the observed pattern of covariation, and (4) the phenomenon of clonal interference among competing genotypes carrying different beneficial mutations. Using these convergences, we have been able to estimate the fitness contribution of the identified mutations and epistatic groups. Keeping in mind statistical uncertainties, these estimates suggest that along with several beneficial mutations of major effect, many other mutations got fixed as part of a group of epistatic mutations.     

Gaia as a complex adaptive system

We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self-organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large-scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary-scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self-regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self-organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life ('Alife') techniques may enable more comprehensive feasibility tests of Gaia.     

External and internal complexity of complex adaptive systems

We introduce concepts of external and internal complexity to analyze the relation between an adaptive system and its environment. We apply this theoretical framework to the construction of models in a cognitive system and the selection between hypotheses through selective observations performed on a data set in a recurrent process and propose a corresponding neural network architecture.     

Parallels among positive-strand RNA viruses, reverse-transcribing viruses and double-stranded RNA viruses

Viruses are divided into seven classes on the basis of differing strategies for storing and replicating their genomes through RNA and/or DNA intermediates. Despite major differences among these classes, recent results reveal that the non-virion, intracellular RNA-replication complexes of some positive-strand RNA viruses share parallels with the structure, assembly and function of the replicative cores of extracellular virions of reverse-transcribing viruses and double-stranded RNA viruses. Therefore, at least four of seven principal virus classes share several underlying features in genome replication and might have emerged from common ancestors. This has implications for virus function, evolution and control.     

TLR-independent induction of dendritic cell maturation and adaptive immunity by negative-strand RNA viruses

TLR signaling leads to dendritic cell (DC) maturation and immunity to diverse pathogens. The stimulation of TLRs by conserved viral structures is the only described mechanism leading to DC maturation after a virus infection. In this report, we demonstrate that mouse myeloid DCs mature normally after in vivo and in vitro infection with Sendai virus (SeV) in the absence of TLR3, 7, 8, or 9 signaling. DC maturation by SeV requires virus replication not necessary for TLR-mediated triggering. Moreover, DCs deficient in TLR signaling efficiently prime for Th1 immunity after infection with influenza or SeV, generating IFN-gamma-producing T cells, CTLs and antiviral Abs. We have previously demonstrated that SeV induces DC maturation independently of the presence of type I IFN, which has been reported to mature DCs in a TLR-independent manner. The data presented here provide evidence for the existence of a novel intracellular pathway independent of TLR-mediated signaling responsible for live virus triggering of DC maturation and demonstrate its critical role in the onset of antiviral immunity. The revelation of this pathway should stimulate invigorating research into the mechanism for virus-induced DC maturation and immunity.     

Biocomplexity: adaptive behavior in complex stochastic dynamical systems

Existing methods of complexity research are capable of describing certain specifics of bio systems over a given narrow range of parameters but often they cannot account for the initial emergence of complex biological systems, their evolution, state changes and sometimes-abrupt state transitions. Chaos tools have the potential of reaching to the essential driving mechanisms that organize matter into living substances. Our basic thesis is that while established chaos tools are useful in describing complexity in physical systems, they lack the power of grasping the essence of the complexity of life. This thesis illustrates sensory perception of vertebrates and the operation of the vertebrate brain. The study of complexity, at the level of biological systems, cannot be completed by the analytical tools, which have been developed for non-living systems. We propose a new approach to chaos research that has the potential of characterizing biological complexity. Our study is biologically motivated and solidly based in the biodynamics of higher brain function. Our biocomplexity model has the following features, (1) it is high-dimensional, but the dimensionality is not rigid, rather it changes dynamically; (2) it is not autonomous and continuously interacts and communicates with individual environments that are selected by the model from the infinitely complex world; (3) as a result, it is adaptive and modifies its internal organization in response to environmental factors by changing them to meet its own goals; (4) it is a distributed object that evolves both in space and time towards goals that is continually re-shaping in the light of cumulative experience stored in memory; (5) it is driven and stabilized by noise of internal origin through self-organizing dynamics. The resulting theory of stochastic dynamical systems is a mathematical field at the interface of dynamical system theory and stochastic differential equations. This paper outlines several possible avenues to analyze these systems. Of special interest are input-induced and noise-generated, or spontaneous state-transitions and related stability issues.     

RNA chaperones encoded by RNA viruses

RNAs are functionally diverse macromolecules whose proper functions rely strictly upon their correct tertiary structures. However, because of their high structural flexibility, correct folding of RNAs is challenging and slow. Therefore, cells and viruses encode a variety of RNA remodeling proteins, including helicases and RNA chaperones. In RNA viruses, these proteins are believed to play pivotal roles in all the processes involving viral RNAs during the life cycle. RNA helicases have been studied extensively for decades, whereas RNA chaperones, particularly virus-encoded RNA chaperones, are often overlooked. This review describes the activities of RNA chaperones encoded by RNA viruses, particularly the ones identified and characterized in recent years, and the functions of these proteins in different steps of viral life cycles, and presents an overview of this unique group of proteins.     

Understanding leukemic hematopoiesis as a complex adaptive system

Normal and abnormal hematopoiesis is working as a complex adaptive system. From this perspective, the development and the behavior of hematopoietic cell lineages appear as a balance between normal and abnormal hematopoiesis in the setting of a functioning or malfunctioning microenvironment under the control of the immune system and the influence of hereditary and environmental events.     

The PDZ domain as a complex adaptive system

Specific protein associations define the wiring of protein interaction networks and thus control the organization and functioning of the cell as a whole. Peptide recognition by PDZ and other protein interaction domains represents one of the best-studied classes of specific protein associations. However, a mechanistic understanding of the relationship between selectivity and promiscuity commonly observed in the interactions mediated by peptide recognition modules as well as its functional meaning remain elusive. To address these questions in a comprehensive manner, two large populations of artificial and natural peptide ligands of six archetypal PDZ domains from the synaptic proteins PSD95 and SAP97 were generated by target-assisted iterative screening (TAIS) of combinatorial peptide libraries and by synthesis of proteomic fragments, correspondingly. A comparative statistical analysis of affinity-ranked artificial and natural ligands yielded a comprehensive picture of known and novel PDZ ligand specificity determinants, revealing a hitherto unappreciated combination of specificity and adaptive plasticity inherent to PDZ domain recognition. We propose a reconceptualization of the PDZ domain in terms of a complex adaptive system representing a flexible compromise between the rigid order of exquisite specificity and the chaos of unselective promiscuity, which has evolved to mediate two mutually contradictory properties required of such higher order sub-cellular organizations as synapses, cell junctions, and others--organizational structure and organizational plasticity/adaptability. The generalization of this reconceptualization in regard to other protein interaction modules and specific protein associations is consistent with the image of the cell as a complex adaptive macromolecular system as opposed to clockwork.     

RNA viruses as vectors for the expression of heterologous proteins

RNA viruses comprise a wide variety of infectious agents, some of which are the cause of disease in humans, animals, and plants. Recombinant DNA technology is now making it feasible to modify these genomes and engineer them to express heterologous proteins. Several different schemes are being employed that depend on the genome organization of the virus and on the strategy of replication of the particular virus. Several different examples are illustrated and potential uses as well as possible problems are discussed. In the future reverse genetics may convert some of these viruses from agents of disease to agents of cure.     

基于复杂适应系统理论的城市规划

全球城市化的快速发展带来了诸如气候变化、海平面上升等一系列的问题,而这些问题的解决归根到底是人与自然如何相处的问题。回顾古代中国和西方哲学中关于人与自然关系的朴素整体论描述,认为近代以来西方自然科学以还原论为中心的方法已经不能很好地解决现实世界中的复杂性问题,城市是一个开放性复杂巨系统,是人类改造自然最彻底的地方,也是面临问题最多的地方。城市的发展是一个自然适应性演进的过程。在城市规划中引入复杂适应系统理论,结合复杂适应系统的7个基本特征,给出了城市复杂适应系统的基本特征,进一步将复杂城市系统分为物质和非物质两大子系统,探讨城市系统适应性主体的交互性、复杂性以及适应和过程机制。以山地城镇规划为例,建立了山地城镇适应性规划框架,并以此框架应用于福建省长汀县城市总体规划的应用实践中,得出城市规划适应自然是城市可持续发展的有效选择。     

Double-stranded RNA is produced by positive-strand RNA viruses and DNA viruses but not in detectable amounts by negative-strand RNA viruses

Double-stranded RNA (dsRNA) longer than 30 bp is a key activator of the innate immune response against viral infections. It is widely assumed that the generation of dsRNA during genome replication is a trait shared by all viruses. However, to our knowledge, no study exists in which the production of dsRNA by different viruses is systematically investigated. Here, we investigated the presence and localization of dsRNA in cells infected with a range of viruses, employing a dsRNA-specific antibody for immunofluorescence analysis. Our data revealed that, as predicted, significant amounts of dsRNA can be detected for viruses with a genome consisting of positive-strand RNA, dsRNA, or DNA. Surprisingly, however, no dsRNA signals were detected for negative-strand RNA viruses. Thus, dsRNA is indeed a general feature of most virus groups, but negative-strand RNA viruses appear to be an exception to that rule.     

RNA viruses and mutations

Actively replicating RNA viruses in nature are continually changing their genetic information by spontaneous mutations. These changes often result in alterations in immune-sensitivity, drug-sensitivity, cell-tropism, and host-range, causing uncontrollability of the pathogen and emerging/re-emerging infections. To better understand the virus changes and develop effective methods to control the moving targets, it is essential to obtain information on changes in viral genomes and proteins. Although information on genetic changes is being accumulated very rapidly, assessment of changes in protein structure and function still requires time-consuming works. In this review, we will overview mutation studies of human immunodeficiency virus and other RNA viruses. In addition, we will introduce recent advances in the computational science and its application on mutation studies and drug development.     

Rice yellow mottle virus, an RNA plant virus, evolves as rapidly as most RNA animal viruses

The rate of evolution of an RNA plant virus has never been estimated using temporally spaced sequence data, by contrast to the information available on an increasing range of animal viruses. Accordingly, the evolution rate of Rice yellow mottle virus (RYMV) was calculated from sequences of the coat protein gene of isolates collected from rice over a 40-year period in different parts of Africa. The evolution rate of RYMV was estimated by pairwise distance linear regression on five phylogeographically defined groups comprising a total of 135 isolates. It was further assessed from 253 isolates collected all over Africa by Bayesian coalescent methods under strict and relaxed molecular clock models and under constant size and skyline population genetic models. Consistent estimates of the evolution rate between 4 x 10(-4) and 8 x 10(-4) nucleotides (nt)/site/year were obtained whatever method and model were applied. The synonymous evolution rate was between 8 x 10(-4) and 11 x 10(-4) nt/site/year. The overall and synonymous evolution rates of RYMV were within the range of the rates of 50 RNA animal viruses, below the average but above the distribution median. Experimentally, in host change studies, substitutions accumulated at an even higher rate. The results show that an RNA plant virus such as RYMV evolves as rapidly as most RNA animal viruses. Knowledge of the molecular clock of plant viruses provides methods for testing a wide range of biological hypotheses.