Spatial pattern formation induced by Gaussian white noise

The ability of Gaussian noise to induce ordered states in dynamical systems is here presented in an overview of the main stochastic mechanisms able to generate spatial patterns. These mechanisms involve: (i) a deterministic local dynamics term, accounting for the local rate of variation of the field variable, (ii) a noise component (additive or multiplicative) accounting for the unavoidable environmental disturbances, and (iii) a linear spatial coupling component, which provides spatial coherence and takes into account diffusion mechanisms. We investigate these dynamics using analytical tools, such as mean-field theory, linear stability analysis and structure function analysis, and use numerical simulations to confirm these analytical results.     

A framework for modelling soil structure dynamics induced by biological activity

Soil degradation is a worsening global phenomenon driven by socio‐economic pressures, poor land management practices and climate change. A deterioration of soil structure at timescales ranging from seconds to centuries is implicated in most forms of soil degradation including the depletion of nutrients and organic matter, erosion and compaction. New soil–crop models that could account for soil structure dynamics at decadal to centennial timescales would provide insights into the relative importance of the various underlying physical (e.g. tillage, traffic compaction, swell/shrink and freeze/thaw) and biological (e.g. plant root growth, soil microbial and faunal activity) mechanisms, their impacts on soil hydrological processes and plant growth, as well as the relevant timescales of soil degradation and recovery. However, the development of such a model remains a challenge due to the enormous complexity of the interactions in the soil–plant system. In this paper, we focus on the impacts of biological processes on soil structure dynamics, especially the growth of plant roots and the activity of soil fauna and microorganisms. We first define what we mean by soil structure and then review current understanding of how these biological agents impact soil structure. We then develop a new framework for modelling soil structure dynamics, which is designed to be compatible with soil–crop models that operate at the soil profile scale and for long temporal scales (i.e. decades, centuries). We illustrate the modelling concept with a case study on the role of root growth and earthworm bioturbation in restoring the structure of a severely compacted soil.     

On detecting interactions between species in population dynamics

If we are to progress out of our current state of uncertainty about the role of interspecific competition in community structure, it is essential that we can distinguish competition from other types of population interaction, and from lack of interaction, in particular case studies. To make such distinctions, it is necessary to quantify the effect of species on each other. One way to do this is to calculate interaction coefficients, and another (only readily applicable in experimental systems) is to plot graphs of N against time and to contrast monocultures with mixed cultures. We show (1) that these methods often appear to give contradictory results, and (2) that the problems are most pronounced when one species has a low equilibrium population size in mixed culture. To resolve the question of whether an interspecific interaction is taking place (and if so, what kind of interaction), it is necessary to apply tests of significance which overcome the problems of serial correlation inherent in all long-term population experiments. We illustrate the use of such tests in the analysis of the results from an experimental Drosophiia system. In the past, this kind of test has generally not been applied, and this raises the question of whether some of the 'classic cases of competition' in the experimental literature were really competition at all.     

Langevin dynamics of conformational transformations induced by the charge–curvature interaction

The role of thermal fluctuations in the conformational dynamics of a single closed filament is studied. It is shown that, due to the interaction between charges and bending degrees of freedom, initially circular chains may undergo transformation to polygonal shape.     

Molecular dynamics simulation of interactions in glycolytic enzymes

Two glycolytic enzymes, phosphoglycerate mutase (PGM) and enolase from Saccharomyces cerevisiae, have been chosen to detect complex formation and possible channeling, using molecular dynamics simulation. The enzymes were separated by 10 angstroms distance and placed in a water-filled box of size 173 x 173 x 173 angstroms. Three different orientations have been investigated. The two initial 3-phosphoglycerate substrate molecules near the active centers of the initial structure of PGM have been replaced with final product (2-phosphoglycerate) molecules, and 150 mM NaCl together with three Mg2+ ions have been added to the system to observe post-catalytic activity under near-physiological conditions. Analysis of interaction energies and conformation changes for 3 nsec simulation indicates that PGM and enolase do show binding affinity between their near active regions, which is necessary for channeling to occur. Interaction of the C-terminal residues Ala239 and Val240 of PGM (which partially "cap" the 2-phosphoglycerate) with enolase also favors the existence of channeling.     

Application of wavelet-based tools to study the dynamics of biological processes

The article makes use of three different examples (sensory information processing in the rat trigeminal complex, intracellular interaction in snail neurons and multimodal dynamics in nephron autoregulation) to demonstrate how modern approaches to time-series analysis based on the wavelet-transform can provide information about the underlying complex biological processes.     

Understanding protein-protein interactions by genetic suppression

Protein-protein interactions influence many cellular processes and it is increasingly being felt that even a weak and remote interplay between two subunits of a protein or between two proteins in a complex may govern the fate of a particular biochemical pathway. In a bacterial system where the complete genome sequence is available, it is an arduous task to assign function to a large number of proteins. It is possible that many of them are peripherally associated with a cellular event and it is very difficult to probe such interaction. However, mutations in the genes that encode such proteins (primary mutations) are useful in these studies. Isolation of a suppressor or a second-site mutation that restores the phenotype abolished by the primary mutation could be an elegant yet simple way to follow a set of interacting proteins. Such a reversion site need not necessarily be geometrically close to the primary mutation site.     

Eco-evolutionary dynamics in herbivorous insect communities mediated by induced plant responses

It is increasingly recognized that the ecology of communities and evolution of species within communities are interdependent, and researchers have been paying attention to this rapidly emerging field of research, i.e., through studies on eco-evolutionary dynamics. Most of the studies on eco-evolutionary dynamics have been concerned with direct trophic interactions. However, community ecologists have shown that trait-mediated indirect effects play an important role in shaping the structure of natural communities. In particular, in terrestrial plant–insect systems, indirect effects mediated through herbivore-induced plant responses are common and have a great impact on the structure of herbivore communities. This review describes eco-evolutionary dynamics in herbivorous insect communities, and specifically focuses on the key role of herbivore-induced plant responses in eco-evolutionary dynamics. First, I review studies on the evolution of herbivore traits relevant to plant induction and discuss evolution in a community context mediated by induced plant responses. Second, I highlight how intraspecific genetic variation or evolution in herbivore traits can influence herbivore community structure. Finally, I propose the hypothetical model that induced plant responses supports eco-evolutionary feedback in herbivore communities. In this review, I argue that the application of the indirect interaction web approaches into studies on eco-evolutionary will provide profound insights into understanding of mechanisms of the generation and maintenance of biodiversity.     

Tracking the dynamics of pathogen interactions: modeling ecological and immune-mediated processes in a two-pathogen single-host system

Traditionally, epidemiological studies have focused on understanding the dynamics of a single pathogen, assuming no interactions with other pathogens. Recently, a large body of work has begun to explore the effects of immune-mediated interactions, arising from cross-immunity and antibody-dependent enhancement, between related pathogen strains. In addition, ecological processes such as a temporary period of convalescence and pathogen-induced mortality have led to the concept of ecological interference between unrelated diseases. There remains, however, the need for a systematic study of both immunological and ecological processes within a single framework. In this paper, we develop a general two-pathogen single-host model of pathogen interactions that simultaneously incorporates these mechanisms. We are then able to mechanistically explore how immunoecological processes mediate interactions between diseases for a pool of susceptible individuals. We show that the precise nature of the interaction can induce either competitive or cooperative associations between pathogens. Understanding the dynamic implications of multi-pathogen associations has potentially important public health consequences. Such a framework may be especially helpful in disentangling the effects of partially cross-immunizing infections that affect populations with a pre-disposition towards immunosuppression such as children and the elderly.     

Frequency-dependent community dynamics driven by sexual interactions

Research in community ecology has tended to focus on trophic interactions (e.g., predation, resource competition) as driving forces of community dynamics, and sexual interactions have often been overlooked. Here we discuss how sexual interactions can affect community dynamics, especially focusing on frequency-dependent dynamics of horizontal communities (i.e., communities of competing species in a single ecological guild). By combining mechanistic and phenomenological models of competition, we place sexual reproduction into the framework of modern coexistence theory. First, we review how population dynamics of two species competing for two resources can be represented by the Lotka–Volterra competition model as well as frequency dynamics, and how niche differentiation and overlap produce negative and positive frequency-dependence (i.e., stable coexistence and priority effect), respectively. Then, we explore two situations where sexual interactions change the frequency-dependence in community dynamics: (1) reproductive interference, that is, negative interspecific interactions due to incomplete species recognition in mating trials, can promote positive frequency-dependence and (2) density-dependent intraspecific adaptation load, that is, reduced population growth rates due to adaptation to intraspecific sexual (or social) interactions, produces negative frequency-dependence. We show how reproductive interference and density-dependent intraspecific adaptation load can decrease and increase niche differences in the framework of modern coexistence theory, respectively. Finally, we discuss future empirical and theoretical approaches for studying how sexual interactions and related phenomena (e.g., reproductive interference, intraspecific adaptation load, and sexual dimorphism) driven by sexual selection and conflict can affect community dynamics.     

Multitype spatial point patterns with hierarchical interactions

Multitype spatial point patterns with hierarchical interactions are considered. Here hierarchical interaction means directionality: points on a higher level of hierarchy affect the locations of points on the lower levels, but not vice versa. Such relations are common, for example, in ecological communities. Interacting point patterns are often modeled by Gibbs processes with pairwise interactions. However, these models are inherently symmetric, and the hierarchy can be acknowledged only when interpreting the results. We suggest the following in allowing the inclusion of the hierarchical structure in the model. Instead of regarding the pattern as a realization of a stationary multivariate point process, we build the pattern one type at a time according to the order of the hierarchy by using nonstationary univariate processes. As interactions connected to points x on a certain level are considered, the effect of the higher levels is interpreted as heterogeneity of the pattern x, and the points on the lower levels are neglected because of the hierarchical structure.     

Unraveling the dynamics of protein interactions with quantitative mass spectrometry

Knowledge of structure and dynamics of proteins and protein complexes is important to unveil the molecular basis and mechanisms involved in most biological processes. Protein complex dynamics can be defined as the changes in the composition of a protein complex during a cellular process. Protein dynamics can be defined as conformational changes in a protein during enzyme activation, for example, when a protein binds to a ligand or when a protein binds to another protein. Mass spectrometry (MS) combined with affinity purification has become the analytical tool of choice for mapping protein–protein interaction networks and the recent developments in the quantitative proteomics field has made it possible to identify dynamically interacting proteins. Furthermore, hydrogen/deuterium exchange MS is emerging as a powerful technique to study structure and conformational dynamics of proteins or protein assemblies in solution. Methods have been developed and applied for the identification of transient and/or weak dynamic interaction partners and for the analysis of conformational dynamics of proteins or protein complexes. This review is an overview of existing and recent developments in studying the overall dynamics of in vivo protein interaction networks and protein complexes using MS-based methods.     

Inferring protein interactions from experimental data by association probabilistic method

To elucidate protein interaction networks is one of the major goals of functional genomics for whole organisms. So far, various computational methods have been proposed for inference of protein-protein interactions. Based on the association method by Sprinzak et al., we propose an association probabilistic method in this short communication to infer protein interactions directly from the experimental data, which outperformed other existing methods in terms of both accuracy and efficiency despite its simple form. Specifically, we show that the association probabilistic method achieves the highest accuracy among the existing approaches for the measures of root-mean-square error and the Pearson correlation coefficient, and also runs much faster than the LP-based method, by experimental dataset in Yeast. Software is available from the authors upon request.     

非线性鸣声对雄性凹耳蛙应答的影响

为了解非线性鸣声对凹耳蛙(Odorrana tormota)应答音的影响以及非线性鸣声是否能够增强鸣声的不可预测性,本研究通过回放非线性鸣声和线性鸣声来刺激陌生雄性凹耳蛙,并记录应答次数及统计分析应答音相关参数。结果表明,回放非线性鸣声时会引起陌生蛙(n=22)更多次数的应答,但两种刺激引起的首次应答时间没有显著差异。对应答音相关参数分析表明,线性鸣声引起的应答音在总时长上比非线性鸣声引起的应答音更长且具有显著差异,而其他声音参数(包括平均基频、最大基频、最小基频、主频)均没有显著差异。推测当陌生雄蛙听到同类鸣叫时,出于保护领地和资源的本能反应,陌生蛙都会第一时间作出反应,因此在两类声音的应答反应时间上并没有区别。而在应答次数上,非线性鸣声引起了凹耳蛙更多次数的应答,可能是由于鸣声中的非线性现象使得声音更加复杂,包含更多信息,容易提高声音接收者对这类声音的关注度。本研究结果表明,凹耳蛙鸣声中包含的非线性现象能够增强其声音的不可预测性,引起陌生蛙产生更多的应答次数。     

Mucin-lectin interactions assessed by flow cytometry

The O-glycosylated domains of mucins and mucin-type glycoproteins contain 50-80% of carbohydrate and possess expanded conformations. Herein, we describe a flow cytometry (FCM) method for determining the carbohydrate-binding specificities of lectins to mucin. Biotinylated mucin was immobilized on streptavidin-coated beads, and the binding specificities of the major mucin sugar chains, as determined by GC-MS and MALDI-ToF, were monitored using fluorescein-labeled lectins. The specificities of lectins toward specific biotinylated glycans were determined as controls. The advantage of flexibility, multiparametric data acquisition, speed, sensitivity, and high-throughput capability makes flow cytometry a valuable tool to study diverse interactions between glycans and proteins.     

南亚热带水土流失地区人工加速植被演替过程

水土流失地区植被在自然条件下从阳生草本到乔灌草复合植被的演替过程常常需要很长的时间,选取适当树种人工造林可以省略先锋物种强阳生草本的发育时间,提早诱发灌木和草本植物发育,大大加速植被恢复演替过程。通过对广东惠州市惠阳区上杨试验站等南亚热带典型水土流失地区的研究发现：自然封育状态下,水土流失地区植被恢复和演替缓慢,25。后植被覆盖度只有35％,且主要以阳生性耐贫瘠的灌木及草本为主,土壤侵蚀仍然比较严重。选择大叶相思树人工造林加速了植被演替进程,控制了水土流失,12a左右植被覆盖度就达90％左右。造林23a左右,林地遮蔽涵养水分和控制侵蚀作用下迅速生长多种当地物种,形成了乔、灌、草、藤、竹多层复合植被。在南亚热带季风气候地区,自然封育状态下严重水土流失区植被恢复至较稳定的次生林阶段需要60a左右的时间;人工造林加速植被演替只需要20a。植树造林是该地区植被恢复发育及控制水土流失的有效措施。     

Zika virus induced cellular remodelling

Zika virus (ZIKV) has been associated with morbidities such as Guillain‐Barré, infant microcephaly, and ocular disease. The spread of this positive‐sense, single‐stranded RNA virus and its growing public health threat underscore gaps in our understanding of basic ZIKV virology. To advance knowledge of the virus replication cycle within mammalian cells, we use serial section 3‐dimensional electron tomography to demonstrate the widespread remodelling of intracellular membranes upon infection with ZIKV. We report extensive structural rearrangements of the endoplasmic reticulum and reveal stages of the ZIKV viral replication cycle. Structures associated with RNA genome replication and virus assembly are observed integrated within the endoplasmic reticulum, and we show viruses in transit through the Golgi apparatus for viral maturation, and subsequent cellular egress. This study characterises in detail the 3‐dimensional ultrastructural organisation of the ZIKV replication cycle stages. Our results show close adherence of the ZIKV replication cycle to the existing flavivirus replication paradigm.