Tree-based networks: characterisations,metrics, and support trees

Phylogenetic networks generalise phylogenetic trees and allow for the accurate representation of the evolutionary history of a set of present-day species whose past includes reticulate events such as hybridisation and lateral gene transfer. One way to obtain such a network is by starting with a (rooted) phylogenetic tree T, called a base tree, and adding arcs between arcs of T. The class of phylogenetic networks that can be obtained in this way is called tree-based networks and includes the prominent classes of tree-child and reticulation-visible networks. Initially defined for binary phylogenetic networks, tree-based networks naturally extend to arbitrary phylogenetic networks. In this paper, we generalise recent tree-based characterisations and associated proximity measures for binary phylogenetic networks to arbitrary phylogenetic networks. These characterisations are in terms of matchings in bipartite graphs, path partitions, and antichains. Some of the generalisations are straightforward to establish using the original approach, while others require a very different approach. Furthermore, for an arbitrary tree-based network N, we characterise the support trees of N, that is, the tree-based embeddings of N. We use this characterisation to give an explicit formula for the number of support trees of N when N is binary. This formula is written in terms of the components of a bipartite graph.

     

Flexible Memory Networks

Networks of neurons in some brain areas are flexible enough to encode new memories quickly. Using a standard firing rate model of recurrent networks, we develop a theory of flexible memory networks. Our main results characterize networks having the maximal number of flexible memory patterns, given a constraint graph on the network’s connectivity matrix. Modulo a mild topological condition, we find a close connection between maximally flexible networks and rank 1 matrices. The topological condition is H ₁(X;ℤ)=0, where X is the clique complex associated to the network’s constraint graph; this condition is generically satisfied for large random networks that are not overly sparse. In order to prove our main results, we develop some matrix-theoretic tools and present them in a self-contained section independent of the neuroscience context.     

Pollinator specialization increases with a decrease in a mass‐flowering plant in networks inferred from DNA metabarcoding

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Contact networks structured by sex underpin sex‐specific epidemiology of infection

Contact networks are fundamental to the transmission of infection and host sex often affects the acquisition and progression of infection. However, the epidemiological impacts of sex‐related variation in animal contact networks have rarely been investigated. We test the hypothesis that sex‐biases in infection are related to variation in multilayer contact networks structured by sex in a population of European badgers Meles meles naturally infected with Mycobacterium bovis. Our key results are that male‐male and between‐sex networks are structured at broader spatial scales than female‐female networks and that in male‐male and between‐sex contact networks, but not female‐female networks, there is a significant relationship between infection and contacts with individuals in other groups. These sex differences in social behaviour may underpin male‐biased acquisition of infection and may result in males being responsible for more between‐group transmission. This highlights the importance of sex‐related variation in host behaviour when managing animal diseases.     

Population sinks resulting from degraded habitats of an obligate life-history pathway

In networks of plant–animal mutualisms, different animal groups interact preferentially with different plants, thus forming distinct modules responsible for different parts of the service. However, what we currently know about seed dispersal networks is based only on birds. Therefore, we wished to fill this gap by studying bat–fruit networks and testing how they differ from bird–fruit networks. As dietary overlap of Neotropical bats and birds is low, they should form distinct mutualistic modules within local networks. Furthermore, since frugivory evolved only once among Neotropical bats, but several times independently among Neotropical birds, greater dietary overlap is expected among bats, and thus connectance and nestedness should be higher in bat–fruit networks. If bat–fruit networks have higher nestedness and connectance, they should be more robust to extinctions. We analyzed 1 mixed network of both bats and birds and 20 networks that consisted exclusively of either bats (11) or birds (9). As expected, the structure of the mixed network was both modular (M = 0.45) and nested (NODF = 0.31); one module contained only birds and two only bats. In 20 datasets with only one disperser group, bat–fruit networks (NODF = 0.53 ± 0.09, C = 0.30 ± 0.11) were more nested and had a higher connectance than bird–fruit networks (NODF = 0.42 ± 0.07, C = 0.22 ± 0.09). Unexpectedly, robustness to extinction of animal species was higher in bird–fruit networks (R = 0.60 ± 0.13) than in bat–fruit networks (R = 0.54 ± 0.09), and differences were explained mainly by species richness. These findings suggest that a modular structure also occurs in seed dispersal networks, similar to pollination networks. The higher nestedness and connectance observed in bat–fruit networks compared with bird–fruit networks may be explained by the monophyletic evolution of frugivory in Neotropical bats, among which the diets of specialists seem to have evolved from the pool of fruits consumed by generalists.     

Catalysis in Reaction Networks

We define catalytic networks as chemical reaction networks with an essentially catalytic reaction pathway: one which is “on” in the presence of certain catalysts and “off” in their absence. We show that examples of catalytic networks include synthetic DNA molecular circuits that have been shown to perform signal amplification and molecular logic. Recall that a critical siphon is a subset of the species in a chemical reaction network whose absence is forward invariant and stoichiometrically compatible with a positive point. Our main theorem is that all weakly-reversible networks with critical siphons are catalytic. Consequently, we obtain new proofs for the persistence of atomic event-systems of Adleman et al., and normal networks of Gnacadja. We define autocatalytic networks, and conjecture that a weakly-reversible reaction network has critical siphons if and only if it is autocatalytic.     

Conserved abundance and topological features in chromatin‐remodeling protein interaction networks

The study of conserved protein interaction networks seeks to better understand the evolution and regulation of protein interactions. Here, we present a quantitative proteomic analysis of 18 orthologous baits from three distinct chromatin‐remodeling complexes in Saccharomyces cerevisiae and Homo sapiens. We demonstrate that abundance levels of orthologous proteins correlate strongly between the two organisms and both networks have highly similar topologies. We therefore used the protein abundances in one species to cross‐predict missing protein abundance levels in the other species. Lastly, we identified a novel conserved low‐abundance subnetwork further demonstrating the value of quantitative analysis of networks.     

Protein evolution on a human signaling network

Background  

The architectural structure of cellular networks provides a framework for innovations as well as constraints for protein evolution. This issue has previously been studied extensively by analyzing protein interaction networks. However, it is unclear how signaling networks influence and constrain protein evolution and conversely, how protein evolution modifies and shapes the functional consequences of signaling networks. In this study, we constructed a human signaling network containing more than 1,600 nodes and 5,000 links through manual curation of signaling pathways, and analyzed the d _N/d _S values of human-mouse orthologues on the network.     

Native and invasive hosts play different roles in host–parasite networks

Parasites are often key players in biological invasions since they can mediate the impact of host invasions or can themselves become invasive species. However, the nature and extent of parasite-mediated invasions are often difficult to delineate. Here, we used individual-based, weighted bipartite networks to study the roles (degrees of interactions of individuals in a modular network according to their within- and among-module connections) played by native and invasive host individuals to their parasite communities. We studied two phylogenetically and ecologically close fish species, Mugil cephalus s.l. and Planiliza haematocheilus (Teleostei: Mugilidae). Planiliza haematocheilus is native to the Sea of Japan and invasive in the Sea of Azov whereas, M. cephalus s.l. is native to both seas. Based on the common evolutionary history that drives native host–parasite networks, we hypothesised that 1) native networks have higher modularity than invaded ones; and 2) invasive hosts in the invaded area play a peripheral role to structure parasite communities. We analysed the whole parasite community and subsets based on transmission strategy and host specificity of the parasite species to establish whether modularity and host roles are related to these features in the native and invaded areas. All networks were found to be modular. However, modularity tended to be higher in networks of the native area rather than those of the invaded area. Host individuals of both fish species played similar roles in the native area, whereas invasive hosts played a peripheral role in the networks of the invaded area. We propose that long-term monitoring of the roles of invasive hosts in parasite communities can be a useful proxy for estimating the maturity of the establishment of the invasive hosts in an ecosystem.     

Arsenic pollution from human activities drives changes in soil microbial community characteristics

Soil arsenic (As) pollution not only decreases plant productivity but also soil quality, in turn hampering sustainable agricultural development. Despite the negative effects of As contamination on rice yield and quality being reported widely, the responses of microbial communities and co-occurrence networks in paddy soil to As pollution have not been explored. Here, based on high-throughput sequencing technologies, we investigated bacterial abundance and diversity in paddy soils with different levels of As contamination, and constructed associated microbial co-occurrence networks. As pollution reduced soil bacterial diversity significantly (p < 0.001). In addition, bioavailable As concentrations were negatively correlated with Actinobacteria and Acidobacteria relative abundance (p < 0.05). Conversely, As pollution had a positive relationship with Chloroflexi, Betaproteobacteria, and Bacteroidetes relative abundance (p < 0.05). Firmicutes relative abundance decreased with an increase in total As concentration. The ecological clusters and key groups in bacterial co-occurrence networks exhibited distinct trends with an increase in As pollution. Notably, Acidobacteria play an important role in maintaining microbial networks in As contaminated soils. Overall, we provide empirical evidence that As contamination influences soil microbial community structure, posing a threat to soil ecosystem health and sustainable agriculture.     

Evolution of a structured cell population endowed with plasticity of traits under constraints on and between the traits

Homeostasis represents the idea that a feature may remain invariant despite changes in some external parameters. We establish a connection between homeostasis and injectivity for reaction network models. In particular, we show that a reaction network cannot exhibit homeostasis if a modified version of the network (which we call homeostasis-associated network) is injective. We provide examples of reaction networks which can or cannot exhibit homeostasis by analyzing the injectivity of their homeostasis-associated networks.

     

Genome-scale reconstruction of the metabolic network in Staphylococcus aureus N315: an initial draft to the two-dimensional annotation

Background  

Several strains of bacteria have sequenced and annotated genomes, which have been used in conjunction with biochemical and physiological data to reconstruct genome-scale metabolic networks. Such reconstruction amounts to a two-dimensional annotation of the genome. These networks have been analyzed with a constraint-based formalism and a variety of biologically meaningful results have emerged. Staphylococcus aureus is a pathogenic bacterium that has evolved resistance to many antibiotics, representing a significant health care concern. We present the first manually curated elementally and charge balanced genome-scale reconstruction and model of S. aureus' metabolic networks and compute some of its properties.     

Promiscuous pollinators—Evidence from an Afromontane sunbird–plant pollen transport network

Sunbirds play a major role in the pollination of Old World nectivorous plants. However, with the exception of the Cape Floristic Region there is a major knowledge gap around African nectivore interaction networks—a stark contrast from the abundance of neotropical hummingbird–plant networks. Here, we describe a sunbird pollen transfer network (PTN) which we use in conjunction with a sunbird flower visitation network (FVN) to explore levels of sunbird specialization within an Afromontane forest habitat. Both networks were generalized compared with similar‐sized hummingbird networks, reflecting the wide range of flower types visited, the generalist diet, and bill characteristics of sunbirds. Three sunbird species from the genus Cinnyris accounted for 85% of flower visits and 77% of all pollen transported. Of the 17 plant species across both networks, 15 are predominantly pollinated by insects while Anthonotha noldeae (Fabaceae–Caesalpinioideae) and Globimetula braunii (Loranthaceae) depend on sunbirds for seed set. Sunbird species average bill lengths varied between 14.5 mm (the variable sunbird) and 23.6 mm (the Green‐headed Sunbird), but, while more pollen was carried on longer bills, we found no evidence for a relationship between bill length and type of flower visited. Both networks were nested. Some specialization was observed in both networks although this does not appear to be driven much by sunbird–flower trait matching. Overall, our results suggest that in contrast to nectivores elsewhere, factors such as phenology and/or environment, rather than morphology, may play important roles in limiting potential sunbird–flower interactions and need further investigation.     

Using ant-based agents for congestion control in ad-hoc wireless sensor networks

Ad-hoc wireless sensor networks suffer from problems of congestion, which lead to packet loss and excessive energy consumption. In this paper, we address the issue of congestion in these networks. We propose a new routing protocol for wireless sensor networks namely Ant-based Routing with Congestion Control (ARCC), which takes into account the congestion of the network at a given instant and proposes to reduce it and then finds the optimum paths between the source and the sink nodes. Simulation results show that ARCC performs better with respect to the throughput, the number of packets lost and the priority performance.     

Ant colony optimization for multicasting in static wireless ad-hoc networks

Nodes of wireless ad-hoc networks are generally equipped with batteries. This makes energy a scarce resource. Therefore, power consumption of network operations is critical and subject to optimization. One of the fundamental problems in ad-hoc networks is multicasting. In this work, we consider the so-called minimum energy multicast (MEM) problem in static ad-hoc networks. This problem can be stated as a combinatorial optimization problem. We develop an ant colony optimization algorithm for networks with omni-directional as well as directional antennas. The results show that our algorithm consistently outperforms existing techniques. This work was supported by grant TIN2007-66523 (FORMALISM) of the Spanish Government, and by the EU project FRONTS (FP7-ICT-2007-1) funded by the European Commission under the FET Proactive Initiative Pervasive Adaptation. In addition, Christian Blum acknowledges support from the Ramón y Cajal program of the Spanish Ministry of Science and Innovation, and Hugo Hernández acknowledges support from the Catalan Government through an FI grant.     

Isolation and Characterization of Kinetoplast DNA Networks and Minicircles from Crithidia fasciculata*

SYNOPSIS. Covalently closed kinetoplast DNA networks have been isolated from stationary phase Crithidia fasciculata cells by a technic involving selective pelleting of the networks at a low centrifugal field. Approximately 62% of the kinetoplast DNA of the cell was recovered free of nuclear DNA by simple differential centrifugation. Purified kinetoplast DNA networks were visualized both in the electron microscope and in the light microscope. Closed networks sedimented as a homogeneous band both in neutral and alkaline sucrose, with an s_20w in neutral sucrose of approximately 5 × 10³. Closed monomeric minicircles were isolated from purified networks by mild sonication and band sedimentation in alkaline sucrose. Several physical properties of closed monomeric minicircles were measured. These included molecular weight, buoyant density in CsCl, superhelix density and sedimentation coefficient.     

植物病原细菌毒性调控网络的研究进展

植物病原细菌通过复杂和精细的全局性调控网络来协调多个层面的毒性决定因子。在不同的植物病原细菌中,这些全局性的毒性调控网络控制着细菌的侵染策略、存活以及在面临寄主植物防卫系统的互作环境中实现成功侵染的病程。本文详细分析了植物病原细菌4个重要属(假单胞菌属、果胶杆菌属、黄单胞菌属和雷尔氏菌属)的模式病原菌主要的毒性调控系统,包括群体感应系统、双组分调控系统、转录激活调控子以及转录后、翻译后的调控机制。在此基础上,重点评价了一些模式菌株全局性毒性调控机制的异同点,总结了一些最新的研究进展,并绘制了精细的网络调控图。这些分析表明,虽然一些相同的调控系统控制着病原菌的毒性,但是在不同种以及种下的亚种或者致病变种中这些调控机制功能各异,对于病原菌全毒性的贡献也存在着明显的差异。