Interaction Networks

Anaerobic digestion (AnD) is a microbiological process that converts organic waste materials into biogas. Because of its high methane content, biogas is a combustible energy source and serves as an important environmental technology commonly used in the management of animal waste generated on large animal farms. Much work has been done on hardware design and process engineering for the generation of biogas. However, little is known about the complexity of the microbiology in this process. In particular, how microbes interact in the digester and eventually breakdown and convert organic matter into biogas is still regarded as a "black box." We used 16S rRNA sequencing as a tool to study the microbial community in laboratory hog waste digesters under tightly controlled conditions, and systematically unraveled the distinct interaction networks of two microbial communities from mesophilic (MAnD) and thermophilic anaerobic digestion (TAnD). Under thermophilic conditions, the well-known association between hydrogen-producing bacteria, e.g., Ruminococcaceae and Prevotellaceae, and hydrotrophic methanogens, Methanomicrobiaceae, was reverse engineered by their interactive topological niches. The inferred interaction network provides a sketch enabling the determination of microbial interactive relationships that conventional strategy of finding differential taxa was hard to achieve. This research is still in its infancy, but it can help to depict the dynamics of microbial ecosystems and to lay the groundwork for understanding how microorganisms cohabit in the anaerobic digester.

Anaerobic digestion (AnD) is a microbiological process that converts organic waste materials into biogas. Because of its high methane content, biogas is a combustible energy source and serves as an important environmental technology commonly used in the management of animal waste generated on large animal farms. Much work has been done on hardware design and process engineering for the generation of biogas. However, little is known about the complexity of the microbiology in this process. In particular, how microbes interact in the digester and eventually breakdown and convert organic matter into biogas is still regarded as a "black box." We used 16S rRNA sequencing as a tool to study the microbial community in laboratory hog waste digesters under tightly controlled conditions, and systematically unraveled the distinct interaction networks of two microbial communities from mesophilic (MAnD) and thermophilic anaerobic digestion (TAnD). Under thermophilic conditions, the well-known association between hydrogen-producing bacteria, e.g., Ruminococcaceae and Prevotellaceae, and hydrotrophic methanogens, Methanomicrobiaceae, was reverse engineered by their interactive topological niches. The inferred interaction network provides a sketch enabling the determination of microbial interactive relationships that conventional strategy of finding differential taxa was hard to achieve. This research is still in its infancy, but it can help to depict the dynamics of microbial ecosystems and to lay the groundwork for understanding how microorganisms cohabit in the anaerobic digester.

O uso das TDIC, quando bem planejado e orientado à construção de aprendizagens significativas, funciona como importante aliado na geração e disseminação de conhecimentos de forma inter-relacional, crítica, criativa e inovadora, conectados às reivindicações da sociedade e das juventudes contemporâneas que há muito não se reconhecem nas metodologias de ensino pautadas no tradicionalismo pedagógico. Palavras-chave: TDIC; Ensino de geografia; Práticas docentes.

Nested structure, in which specialists interact with subsets of species with which generalists interact, has been repeatedly found in networks of mutualistic interactions and thus is considered a general feature of mutualistic communities. However, it is uncertain how exclusive nested structure is for mutualistic communities since few studies have evaluated nestedness in other types of networks. Here, we show that 31 published food webs consist of bipartite subwebs that are as highly nested as mutualistic networks, contradicting the hypothesis that antagonistic interactions disfavor nested structure. Our findings suggest that nested networks may be a common pattern of communities that include resource-consumer interactions. In contrast to the hypothesis that nested structure enhances biodiversity in mutualistic communities, we also suggest that nested food webs increase niche overlap among consumers and thus prevent their coexistence. We discuss potential mechanisms for the emergence of nested structure in food webs and other types of ecological networks.

This study compares the variation of richness, abundance, and diversity of butterfly species for vegetation communities along an elevational gradient and during different seasons in the Priority Region for Conservation of Biodiversity, Sierra Chiquita, located in the northeast of Mexico. We also analyze the influence of environmental variables on the abundance and richness of butterfly species. Seven sampling sites were established based on criteria of vegetation distribution per altitudinal gradient. Sampling was on a monthly basis and carried out in six permanent plots at each site, using an aerial entomological net during November 2015 to October 2016. A total of 38,011 specimens, representing six families and 195 species, were collected. All parameter values showed significant differences across sites, except between thorn forest and gallery forest. Seasonality effect was absent on richness and diversity species; however, for species abundance, the differences between dry season and rainy season were significantly different in each site except for the comparison of thorn forest and gallery forest. The association between the environmental variables and butterfly communities in the elevational gradient was significant, being the dew point, the solar radiation, the canopy leaf area, and the number of flowering plants the most important variables. The present work represents an important contribution of the vegetation communities variation in richness, abundance, and diversity of butterflies in the northeast of Mexico. These results highlight the importance of the conservation of this heterogeneous habitat and establish reference data for the diurnal Lepidoptera fauna of the region.

It is generally deemed that doping is a must for polymeric materials to achieve their high thermoelectric performance. We herein present the first report that intrinsically metallic behaviors and high-performance thermoelectric power factors can coexist within doping-free linear-backbone conducting polymers, poly(nickel-ethylenetetrathiolate) and its analogs. On the basis of density functional calculations, we have corroborated that four crystalline π- d conjugated transition-metal coordination polymers, including poly(Ni-CS), poly(Ni-CSe), poly(Pd-CS) and poly(Pt-CS) exhibit intrinsically metallic behavior arising from the formation of dense intermolecular interaction networks between sulfur/selenium atoms. They show moderate carrier concentrations (10-10 cm) and decent conductivities (10-10 S cm), among which, poly(Ni-CS), poly(Ni-CSe) and poly(Pd-CS) possess high power factors (∼10 μW m K).

This paper investigates questions related to the modularity in discrete models of biological interaction networks. We develop a theoretical framework based on the analysis of their asymptotic dynamics. More precisely, we exhibit formal conditions under which agents of interaction networks can be grouped into modules. As a main result, we show that the usual decomposition in strongly connected components fulfils the conditions of being a modular organisation. Furthermore, we point out that our framework enables a finer analysis providing a decomposition in elementary modules.

Despite the importance of coral microbiomes for holobiont persistence, the interactions among these are not well understood. In particular, knowledge of the co-occurrence and taxonomic importance of specific members of the microbial core, as well as patterns of specific mobile genetic elements (MGEs), is lacking. We used seawater and mucus samples collected from colonies on two reefs located in Bahia, Brazil, to disentangle their associated bacterial communities, intertaxa correlations, and plasmid patterns. Proxies for two broad-host-range (BHR) plasmid groups, IncP-1β and PromA, were screened. Both groups were significantly (up to 252 and 100%, respectively) more abundant in coral mucus than in seawater. Notably, the PromA plasmid group was detected only in coral mucus samples. The core bacteriome of  mucus was composed primarily of members of the Proteobacteria, followed by those of Firmicutes. Significant host specificity and co-occurrences among different groups of the dominant...

Coastal hypoxia is increasing worldwide in response to human‐caused changes in global climate and biogeochemical cycles. In this paper, we view anthropogenic trends in coastal hypoxia through the lens of disturbance ecology and complexity theory. Complexity theory provides a framework for describing how estuaries and other coastal aquatic ecosystems respond to hypoxia by understanding feedback loops. Can it also be valuable in understanding how these ecosystems behave under shifting (i.e., unnatural) disturbance regimes? When viewed as a disturbance regime, shifts in the spatial (areal extent and fragmentation) and temporal (frequency and duration of events) characteristics of coastal hypoxia can be used to track changes into a non‐stationary future. Here, we consider options for increasing the resilience of coastal aquatic ecosystems to future, unnatural hypoxic regimes. To start, we define desirable states as ecosystems with long trophic chains and slow nutrient and carbon dynamic...

Despite a growing body of evidence, the role of the gut microbiome in cardiovascular diseases is still unclear. Here, we present a systems-genome-wide and metagenome-wide association study on plasma concentrations of 92 cardiovascular-disease-related proteins in the population cohort LifeLines-DEEP. We identified genetic components for 73 proteins and microbial associations for 41 proteins, of which 31 were associated to both. The genetic and microbial factors identified mostly exert additive effects and collectively explain up to 76.6% of inter-individual variation (17.5% on average). Genetics contribute most to concentrations of immune-related proteins, while the gut microbiome contributes most to proteins involved in metabolism and intestinal health. We found several host-microbe interactions that impact proteins involved in epithelial function, lipid metabolism, and central nervous system function. This study provides important evidence for a joint genetic and microbial effect i...

We studied the saproxylic beetle community inhabiting deadwood in remnants of riparian cloud forests in "La Antigua" basin, in central Veracruz (Mexico). We assessed the influence of deadwood features (tree species, trunk position, trunk diameter, trunk volume and decomposition stages) on saproxylic beetle diversity. In order to assess the stability of beetle species-deadwood interactions, we also analyzed the ecological networks structure. A total of 63 deadwood trunks, belonging to four tree species, were sampled by standardized hand-collection throughout well-preserved remnants of riparian cloud forest. We found that tree species and deadwood decay stage are the main drivers that determine the diversity and stability of saproxylic beetle species interactions. Our results indicate that Quercus corrugata is the main tree species in terms of maintaining the significantly highest saproxylic beetle diversity, but with no stable interactions (saproxylic beetle-deadwood). A nested network structure was detected for Clethra mexicana and Liquidambar styraciflua, with a pool of core (generalist) saproxylic beetle species. We observed that beetle diversity from the early and late deadwood stages comprises distinct assemblages and the four stages of decomposition showed a nested network structure. During deadwood succession, community composition and guilds changed among networks; the early successional stage had more specialized xylophagous beetles, while other guilds (mycophagous, saprophagous and zoophagous) arrive later and become the core species in the advanced stages of decomposition networks. Heliscus tropicus (Passalidae) is a key species constituting the core of all of the networks and could be considered an ecosystem engineer in cloud forests. By exploring links between saproxylic beetles and deadwood characteristics, we can further our understanding of species interaction in order to develop management strategies oriented towards the protection of species and their habitats in this threatened ecosystem.

Species interaction networks have been described as "the architecture of biodiversity" because of their importance for community composition and dynamics (Jordano et al. 2006, Bascompte and Jordano 2007). Networks can be analyzed to identify keystone species (Christianou and Ebenman 2005), monitor biodiversity (Forup et al. 2008), and determine the functional roles of nonnative species (Kaiser-Bunbury et al. 2010, Tylianakis et al. 2010). Network analyses are increasingly being used to understand how communities are changing as a result of species invasions or extinctions (

Urban planning is important to guarantee the quality of life for society, as it proposes spatial planning and problem solving, especially those related to land use. Thus, it was proposed to perform an evaluation of actions that promote and/or accelerate the erosive processes on a hillside located in Island of Itamaracá/BR. The "interaction networks" and "land use maps" techniques were used in combination, which resulted in a more accurate environmental assessment, as well as the use of models for future estimates. The results pointed to medium risk for the environmental indicators of "occupation types" and evidence of collapse", and high risk for "urban density" and "vegetation" indicators. It has also been predicted that over the years, the urban sprawl in the area will continue to grow until it reaches stability due to the total occupation of useful areas as well as that the growth rate for vegetation will be negative. Thus, there is a need to mitigate environmental damage in the short term, in order to avoid the occurrence of accidents in the hillside area.

The construction and analysis of networks is increasingly widespread in biological research. We have developed esyN (''easy networks'') as a free and open source tool to facilitate the exchange of biological network models between researchers. esyN acts as a searchable database of user-created networks from any field. We have developed a simple companion web tool that enables users to view and edit networks using data from publicly available databases. Both normal interaction networks (graphs) and Petri nets can be created. In addition to its basic tools, esyN contains a number of logical templates that can be used to create models more easily. The ability to use previously published models as building blocks makes esyN a powerful tool for the construction of models and network graphs. Users are able to save their own projects online and share them either publicly or with a list of collaborators. The latter can be given the ability to edit the network themselves, allowing online collaboration on network construction. esyN is designed to facilitate unrestricted exchange of this increasingly important type of biological information. Ultimately, the aim of esyN is to bring the advantages of Open Source software development to the construction of biological networks.

Plant-animal interactions occur in a community context of dynamic and complex ecological interactive networks. The understanding of who interacts with whom is a basic information, but the outcomes of interactions among associates are fundamental to draw valid conclusions about the functional structure of the network. Ecological networks studies in general gave little importance to know the true outcomes of interactions and how they may change over time. We evaluate the dynamic of an interaction network between ants and plants with extrafloral nectaries, by verifying the temporal variation in structure and outcomes of mutualism for the plant community (leaf herbivory). To reach this goal, we used two tools: bipartite network analysis and experimental manipulation. The networks exhibited the same general pattern as other mutualistic networks: nestedness, asymmetry and low specialization and this pattern was maintained over time, but with internal changes (species degree, connectance and ant abundance). These changes influenced the protection effectiveness of plants by ants, which varied over time. Our study shows that interaction networks between ants and plants are dynamic over time, and that these alterations affect the outcomes of mutualisms. In addition, our study proposes that the set of single systems that shape ecological networks can be manipulated for a greater understanding of the entire system.

We studied the saproxylic beetle community inhabiting deadwood in remnants of riparian cloud forests in "La Antigua" basin, in central Veracruz (Mexico). We assessed the influence of deadwood features (tree species, trunk position, trunk diameter, trunk volume and decomposition stages) on saproxylic beetle diversity. In order to assess the stability of beetle species-deadwood interactions, we also analyzed the ecological networks structure. A total of 63 deadwood trunks, belonging to four tree species, were sampled by standardized hand-collection throughout well-preserved remnants of riparian cloud forest. We found that tree species and deadwood decay stage are the main drivers that determine the diversity and stability of saproxylic beetle species interactions. Our results indicate that Quercus corrugata is the main tree species in terms of maintaining the significantly highest saproxylic beetle diversity, but with no stable interactions (saproxylic beetle-deadwood). A nested network structure was detected for Clethra mexicana and Liquidambar styraciflua, with a pool of core (generalist) saproxylic beetle species. We observed that beetle diversity from the early and late deadwood stages comprises distinct assemblages and the four stages of decomposition showed a nested network structure. During deadwood succession, community composition and guilds changed among networks; the early successional stage had more specialized xylophagous beetles, while other guilds (mycophagous, saprophagous and zoophagous) arrive later and become the core species in the advanced stages of decomposition networks. Heliscus tropicus (Passalidae) is a key species constituting the core of all of the networks and could be considered an ecosystem engineer in cloud forests. By exploring links between saproxylic beetles and deadwood characteristics, we can further our understanding of species interaction in order to develop management strategies oriented towards the protection of species and their habitats in this threatened ecosystem.

Coastal hypoxia is increasing worldwide in response to human‐caused changes in global climate and biogeochemical cycles. In this paper, we view anthropogenic trends in coastal hypoxia through the lens of disturbance ecology and complexity theory. Complexity theory provides a framework for describing how estuaries and other coastal aquatic ecosystems respond to hypoxia by understanding feedback loops. Can it also be valuable in understanding how these ecosystems behave under shifting (i.e., unnatural) disturbance regimes? When viewed as a disturbance regime, shifts in the spatial (areal extent and fragmentation) and temporal (frequency and duration of events) characteristics of coastal hypoxia can be used to track changes into a non‐stationary future. Here, we consider options for increasing the resilience of coastal aquatic ecosystems to future, unnatural hypoxic regimes. To start, we define desirable states as ecosystems with long trophic chains and slow nutrient and carbon dynamic...

Despite a growing body of evidence, the role of the gut microbiome in cardiovascular diseases is still unclear. Here, we present a systems-genome-wide and metagenome-wide association study on plasma concentrations of 92 cardiovascular-disease-related proteins in the population cohort LifeLines-DEEP. We identified genetic components for 73 proteins and microbial associations for 41 proteins, of which 31 were associated to both. The genetic and microbial factors identified mostly exert additive effects and collectively explain up to 76.6% of inter-individual variation (17.5% on average). Genetics contribute most to concentrations of immune-related proteins, while the gut microbiome contributes most to proteins involved in metabolism and intestinal health. We found several host-microbe interactions that impact proteins involved in epithelial function, lipid metabolism, and central nervous system function. This study provides important evidence for a joint genetic and microbial effect i...

Despite a growing body of evidence, the role of the gut microbiome in cardiovascular diseases is still unclear. Here, we present a systems-genome-wide and metagenome-wide association study on plasma concentrations of 92 cardiovascular-disease-related proteins in the population cohort LifeLines-DEEP. We identified genetic components for 73 proteins and microbial associations for 41 proteins, of which 31 were associated to both. The genetic and microbial factors identified mostly exert additive effects and collectively explain up to 76.6% of inter-individual variation (17.5% on average). Genetics contribute most to concentrations of immune-related proteins, while the gut microbiome contributes most to proteins involved in metabolism and intestinal health. We found several host-microbe interactions that impact proteins involved in epithelial function, lipid metabolism, and central nervous system function. This study provides important evidence for a joint genetic and microbial effect i...

As molecular tools for assessing trophic interactions become common, research is increasingly focused on the construction of interaction networks. Here we demonstrate three key methods for incorporating DNA data into network ecology and discuss analytical considerations using a model consisting of plants, insects, bats and their parasites from the Costa Rican dry forest. The simplest method involves the use of Sanger sequencing to acquire long sequences to validate or refine field identifications, for example of bats and their parasites, where one specimen yields one sequence and one identification. This method can be fully quantified and resolved and these data resemble traditional ecological networks. For more complex taxonomic identifications, we target multiple DNA loci e.g. from a seed or fruit pulp sample in faeces. These networks are also well resolved but gene targets vary in resolution and quantification is difficult. Finally for mixed templates such as faecal contents of insectivorous bats we use DNA metabarcoding targeting two sequence lengths (157bp, 407bp) of one gene region and a MOTU, BLAST and BIN association approach to resolve nodes. This network type is complex to generate and analyse and we discuss the implications of this type of resolution on network analysis. Using these data we construct the first molecular-based network of networks containing 3304 interactions between 762 nodes of 8 trophic functions and involving parasitic, mutualistic, and predatory interactions. We provide a comparison of the relative strengths and weaknesses of these data types in network ecology.

Coastal hypoxia is increasing worldwide in response to human-caused changes in global climate and biogeochemical cycles. In this paper, we view anthropogenic trends in coastal hypoxia through the lens of disturbance ecology and complexity theory. Complexity theory provides a framework for describing how estuaries and other coastal aquatic ecosystems respond to hypoxia by understanding feedback loops. Can it also be valuable in understanding how these ecosystems behave under shifting (i.e., unnatural) disturbance regimes? When viewed as a disturbance regime, shifts in the spatial (areal extent and fragmentation) and temporal (frequency and duration of events) characteristics of coastal hypoxia can be used to track changes into a non-stationary future. Here, we consider options for increasing the resilience of coastal aquatic ecosystems to future, unnatural hypoxic regimes. To start, we define desirable states as ecosystems with long trophic chains and slow nutrient and carbon dynamics that produce many ecosystem services. We then work backward to describe circumstances dominated by positive feedbacks that can lead ecosystems toward an undesirable state (i.e., depauperate communities and chemically reduced sediments). Processes of degradation and recovery can be understood in the context of island biogeography whereby species diversity in habitats fragmented by hypoxia is determined by the balance between rapid local extinction, slow recolonization from the edges of hypoxic patches, and opportunities for ecological succession during between disturbance events. We review potential future changes associated with changing global climate and highlight ways to enhance coastal resilience. In addition to efforts to slow climate change, potential interventions include reduced nutrient and carbon loadings from rivers, restoration of aquatic vegetation, and managing for key species, including those that promote sediment oxygenation, that enhance water clarity, or that promote grazing on epiphytic algae through top-down control.

Land-use change in terrestrial environments is one of the main threats to biodiversity. The study of ant-plant networks has increased our knowledge of the diversity of interactions and structure of these communities; however, little is known about how land-use change affects ant-plant networks. Here we determine whether the change in land use, from native oak forest to induced grassland, affected the network properties of ant-plant networks in a temperate forest in Mexico. We hypothesize that the disturbed vegetation will be more nested and generalized due to the addition of generalist species to the network. The oak forest network comprises 47 plant species and 11 ant species, while the induced grassland network has 35 and 13, respectively. Floral nectar was the resource used most intensely by the ants in both vegetation types. The ant-plant network of the induced grassland was significantly more nested and generalist than that of the oak forest; however, none of the networks were ...

Urban planning is important to guarantee the quality of life for society, as it proposes spatial planning and problem solving, especially those related to land use. Thus, it was proposed to perform an evaluation of actions that promote and/or accelerate the erosive processes on a hillside located in Island of Itamaracá/BR. The "interaction networks" and "land use maps" techniques were used in combination, which resulted in a more accurate environmental assessment, as well as the use of models for future estimates. The results pointed to medium risk for the environmental indicators of "occupation types" and evidence of collapse", and high risk for "urban density" and "vegetation" indicators. It has also been predicted that over the years, the urban sprawl in the area will continue to grow until it reaches stability due to the total occupation of useful areas as well as that the growth rate for vegetation will be negative. Thus, there is a need to mitigate environmental damage in the short term, in order to avoid the occurrence of accidents in the hillside area.

Despite a growing body of evidence, the role of the gut microbiome in cardiovascular diseases is still unclear. Here, we present a systems-genome-wide and metagenome-wide association study on plasma concentrations of 92 cardiovascular-disease-related proteins in the population cohort LifeLines-DEEP. We identified genetic components for 73 proteins and microbial associations for 41 proteins, of which 31 were associated to both. The genetic and microbial factors identified mostly exert additive effects and collectively explain up to 76.6% of inter-individual variation (17.5% on average). Genetics contribute most to concentrations of immune-related proteins, while the gut microbiome contributes most to proteins involved in metabolism and intestinal health. We found several host-microbe interactions that impact proteins involved in epithelial function, lipid metabolism, and central nervous system function. This study provides important evidence for a joint genetic and microbial effect i...

Biomedical knowledge graphs such as STITCH, SIDER, and Drugbank provide the basis for the discovery of associations between biomedical entities, e.g., interactions between drugs and targets. Link prediction is a paramount task and represents a building block for supporting knowledge discovery. Although several approaches have been proposed for effectively predicting links, the role of semantics has not been studied in depth. In this work, we tackle the problem of discovering interactions between drugs and targets, and propose SimTransE, a machine learning-based approach that solves this problem effectively. SimTransE relies on translating embeddings to model drug-target interactions and values of similarity across them. Grounded on the vectorial representation of drug-target interactions, SimTransE is able to discover novel drug-target interactions. We empirically study SimTransE using state-ofthe-art benchmarks and approaches. Experimental results suggest that SimTransE is competitive with the state of the art, representing, thus, an effective alternative for knowledge discovery in the biomedical domain.

Background Atherosclerosis affects aorta, coronary, carotid, and iliac arteries most frequently than any other body vessel. There may be common molecular pathways sustaining this process. Plaque presence and diffusion is revealed by circulating factors that can mediate systemic reaction leading to plaque rupture and thrombosis. Results We used DNA microarrays and meta-analysis to study how the presence of calcified plaque modifies human coronary and carotid gene expression. We identified a series of potential human atherogenic genes that are integrated in functional networks involved in atherosclerosis. Caveolae and JAK/STAT pathways, and S100A9/S100A8 interacting proteins are certainly involved in the development of vascular disease. We found that the system of caveolae is directly connected with genes that respond to hormone receptors, and indirectly with the apoptosis pathway. Cytokines, chemokines and growth factors released in the blood flux were investigated in parallel. High ...

1. Several studies have recently focused on the structure of ecological networks involving ants and plants with extrafloral nectaries; however, little is known about the effects of temporal variation in resource abundance on the structure of ant-plant networks mediated by floral nectar. 2. In this study, it was evaluated how strong seasonality in resource availability in a semi-arid tropical environment affects the structure of ant-flower networks. We recorded ants collecting floral nectar during two seasons (from December 2009 to January 2013): dry and green seasons. Then, we built interaction networks for flower-visiting ants in the Brazilian Caatinga separately for each combination of transect and season. 3. In general, strong seasonality directly influenced patterns of ant-flower interactions and the overall complexity of these ecological networks. During the dry season, networks were more connected, less modular, and exhibited greater niche overlap of flower-visiting ants than during the green season. Moreover, resource utilisation by ants during the dry season tended to be more aggregated. These findings indicate that during the dry season, ant species tended to share many resource bases, probably owing to lower overall resource availability during this season. Species composition of the ant network component was highly season specific; however, a central core of highly generalised ants was present during both seasons. 4. The stability of this central core between seasons could strongly affect the ecological and evolutionary dynamics of these interaction networks. This study contributes to the understanding of the structure and dynamics of ant-flower interactions in extremely seasonal environments.

Background: Prioritization methods have become an useful tool for mining large amounts of data to suggest promising hypotheses in early research stages. Particularly, network-based prioritization tools use a network representation for the interactions between different biological entities to identify novel indirect relationships. However, current network-based prioritization tools are strongly tailored to specific domains of interest (e.g. genedisease prioritization) and they do not allow to consider networks with more than two types of entities (e.g. genes and diseases). Therefore, the direct application of these methods to accomplish new prioritization tasks is limited. Results: This work presents ProphNet, a generic network-based prioritization tool that allows to integrate an arbitrary number of interrelated biological entities to accomplish any prioritization task. We tested the performance of ProphNet in comparison with leading network-based prioritization methods, namely rcNet and DomainRBF, for gene-disease and domain-disease prioritization, respectively. The results obtained by ProphNet show a significant improvement in terms of sensitivity and specificity for both tasks. We also applied ProphNet to disease-gene prioritization on Alzheimer, Diabetes Mellitus Type 2 and Breast Cancer to validate the results and identify putative candidate genes involved in these diseases. Conclusions: ProphNet works on top of any heterogeneous network by integrating information of different types of biological entities to rank entities of a specific type according to their degree of relationship with a query set of entities of another type. Our method works by propagating information across data networks and measuring the correlation between the propagated values for a query and a target sets of entities. ProphNet is available at: http://genome2.ugr.es/prophnet. A Matlab implementation of the algorithm is also available at the website.

Desde la perspectiva del Análisis de Redes y del Aprendizaje del Paisaje, se evalúa el registro arqueológico correspondiente a la transición Pleistoceno-Holoceno del centro de Argentina (ca. 11000-9000 AP). Para ello, se analiza la circulación de materias primas líticas utilizadas para la elaboración de instrumentos, así como el uso de los recursos simbólicos organizados por medio del estilo de las puntas de proyectil. Se considera que las interrelaciones sociales poseen una importancia vital para el mantenimiento de la continuidad social y el éxito de los procesos de colonización inicial de una determinada región. En toda el área de estudio, el cuarzo es la materia prima lítica de mayor disponibilidad; sin embargo, se destaca el uso de rocas silíceas para las puntas de proyectil y algunos otros artefactos. Fuentes potenciales de estas rocas fueron identificadas en las Sierras Centrales (provincias de Córdoba y San Luis). En base a estas evidencias, y al modelo de yacencia de rocas ...

Background: Understanding the evolution of biological networks can provide insight into how their modular structure arises and how they are affected by environmental changes. One approach to studying the evolution of these networks is to reconstruct plausible common ancestors of present-day networks, allowing us to analyze how the topological properties change over time and to posit mechanisms that drive the networks' evolution. Further, putative ancestral networks can be used to help solve other difficult problems in computational biology, such as network alignment. Results: We introduce a combinatorial framework for encoding network histories, and we give a fast procedure that, given a set of gene duplication histories, in practice finds network histories with close to the minimum number of interaction gain or loss events to explain the observed present-day networks. In contrast to previous studies, our method does not require knowing the relative ordering of unrelated duplication events. Results on simulated histories and real biological networks both suggest that common ancestral networks can be accurately reconstructed using this parsimony approach. A software package implementing our method is available under the Apache 2.0 license at http://cbcb.umd.edu/kingsford-group/parana. Conclusions: Our parsimony-based approach to ancestral network reconstruction is both efficient and accurate. We show that considering a larger set of potential ancestral interactions by not assuming a relative ordering of unrelated duplication events can lead to improved ancestral network inference.

Despite the importance of coral microbiomes for holobiont persistence, the interactions among these are not well understood. In particular, knowledge of the co-occurrence and taxonomic importance of specific members of the microbial core, as well as patterns of specific mobile genetic elements (MGEs), is lacking. We used seawater and mucus samples collected from colonies on two reefs located in Bahia, Brazil, to disentangle their associated bacterial communities, intertaxa correlations, and plasmid patterns. Proxies for two broad-host-range (BHR) plasmid groups, IncP-1β and PromA, were screened. Both groups were significantly (up to 252 and 100%, respectively) more abundant in coral mucus than in seawater. Notably, the PromA plasmid group was detected only in coral mucus samples. The core bacteriome of  mucus was composed primarily of members of the Proteobacteria, followed by those of Firmicutes. Significant host specificity and co-occurrences among different groups of the dominant...

Ecological communities are composed of species that interact with each other forming complex interaction networks. Although interaction networks have been usually treated as static entities, interactions show high levels of temporal variation, mainly due to temporal species turnover. Changes in taxonomic composition are likely to bring about changes in functional trait composition. Because functional traits influence the likelihood that two species interact, temporal changes in functional composition and structure may ultimately affect interaction network structure. Here, we study the seasonality (spring vs. summer) in a community of cavity-nesting solitary bees and wasps ('hosts') and their nest associates ('parasitoids'). We analyze seasonal changes in taxonomic compostion and structure, as well as in functional traits, of the host and parasitoid communities. We also analyze whether these changes result in changes in percent parasitism and interaction network structure. Our host and parasitoid communities are strongly seasonal. Host species richness increases from spring to summer. This results in important seasonal changes in functional composition of the host community. The spring community (almost exclusively composed of bees) is characterized by large, univoltine, adult-wintering host species. The summer community (composed of both bees and wasps) is dominated by smaller, bivoltine, prepupa-wintering species. Host functional diversity is higher in summer than in spring. Importantly, these functional changes are not only explained by the addition of wasp species in summer. Functional changes in the parasitoid community are much less pronounced, probably due to the lower parasitoid species turnover. Despite these important taxonomic and functional changes, levels of parasitism did not change across seasons. Two network metrics (generality and interaction evenness) increased from spring to summer. These changes can be explained by the seasonal increase in species richness (and therefore network size). The seasonal shift from a bee-dominated community in spring to a wasp-dominated community in summer suggests a change in ecosystem function, with emphasis on pollination in spring to emphasis on predation in summer.

In mammals, cardiomyocytes rapidly proliferate in the fetus and continue to do so for a few more days after birth. These cardiomyocytes then enter into growth arrest but the detailed molecular mechanisms involved have not been fully elucidated. We have addressed this issue by comparing the transcriptomes of 2-day-old (containing dividing cardiomyocytes) with 13-day-old (containing growth arrested cardiomyocytes) postnatal mouse hearts. We performed comparative microarray analysis on the heart tissues and then conducted Functional annotation, Gene ontology, KEGG pathway and Gene Set enrichment analyses on the differentially expressed genes. The bioinformatics analysis revealed that gene ontology categories associated with the "cell cycle", "DNA replication", "chromosome segregation" and "microtubule cytoskeleton" were down-regulated. Inversely, "immune response", "extracellular matrix", "cell differentiation" and "cell membrane" were up-regulated. Ingenuity Pathways Analysis (IPA) has revealed that GATA4, MYH7 and IGF1R were the key drivers of the gene interaction networks. In addition, Regulator Effects network analysis suggested that TASP1, TOB1, C1orf61, AIF1, ROCK1, TFF2 and miR503-5p may be acting on the cardiomyocytes in 13-day-old mouse hearts to inhibit cardiomyocyte proliferation and G1/S phase transition. RT-qPCR was used to validate genes which were differentially expressed and genes that play a prominent role in the pathways and interaction networks that we identified. In sum, our integrative analysis has provided more insights into the transcriptional regulation of cardiomyocyte exit from the cell cycle during postnatal heart development. The results also pinpoint potential regulators that could be used to induce growth arrested cardiomyocytes to proliferate in the infarcted heart.

In 2016, day butterflies were tracked in order to establish the importance of 33 edge effects (EB) formed by three traditional agroforestry systems immersed in a fragmented mesophilic forest in Xochitla, Mixtla de Altamirano, Veracruz. Systematic sampling and counting in points with fixed radius were established: the analyzes were carried out by: A) families with EB; B) subfamilies with EB; C) families by sampling; and D) subfamilies by sampling. Wealth and relative abundance were assessed using Jacknife1 and diversity with Shannon-Wiener. Kruskal-Wallis for the three indices, Cluster (wealth and abundance) and  (abundance). Jacknife1 showed values: 70.62; 47.6; 96.66, 80.27%. There were no differences: F= 16, p= 0.724; F= 9, p= 0.4966; F= 20, p= 0.6584; F= 13, p= 0.5953. Cluster exhibited 3 to 5 amalgamations. The IAR presented minimum-maximum average values of 0.001-0.578. There were no discrepancies: F= 26, p= 0.5642; F= 20, p= 0.6271; F= 22, p= 0.8414; F= 30, p= 0.4376. Cluster...

The integration of atomic-resolution experimental and computational methods offers the potential for elucidating key aspects of protein folding that are not revealed by either approach alone. Here, we combine equilibrium NMR measurements of thermal unfolding and long molecular dynamics simulations to investigate the folding of gpW, a protein with two-state-like, fast folding dynamics and cooperative equilibrium unfolding behavior. Experiments and simulations expose a remarkably complex pattern of structural changes that occur at the atomic level and from which the detailed network of residue−residue couplings associated with cooperative folding emerges. Such thermodynamic residue−residue couplings appear to be linked to the order of mechanistically significant events that take place during the folding process. Our results on gpW indicate that the methods employed in this study are likely to prove broadly applicable to the fine analysis of folding mechanisms in fast folding proteins.

Constructing ecological networks has become an indispensable approach in understanding how different taxa interact. However, the methods used to generate data in network research varies widely among studies, potentially limiting our ability to compare results meaningfully. In particular, methods of classifying nodes vary in their precision, likely altering the architecture of the network studied. For example, rather than being classified as Linnaean species, taxa are regularly assigned to morphospecies in observational studies, or to Molecular Operational Taxonomic Units (MOTUs) in molecular studies, with the latter defined based on an arbitrary threshold of sequence similarity. Although the use of MOTUs in ecological networks holds great potential, especially for allowing rapid construction of large datasets of interactions, it is unclear how the choice of clustering threshold can influence the conclusions obtained. To test the impact of taxonomic precision on network architecture, we obtained and analyzed 16 datasets of ecological interactions, inferred from metabarcoding and observations. Our comparisons of networks constructed under a range of sequence thresholds for assigning taxa demonstrate that even small changes in node resolution can cause wide variation in almost all key metric values. Moreover, relative values of commonly used metrics such as robustness were seen to fluctuate continuously with node resolution, thereby potentially causing error in conclusions drawn when comparing multiple networks. In observational networks, we found that changing node resolution could, in some cases, lead to substantial changes to measurements of network topology. Overall, our findings highlight the importance of classifying nodes to the greatest precision possible, and demonstrate the need for caution when comparing networks that differ with respect to node resolution, even where taxonomic groups and interaction types are similar. In such cases, we Page 2 of 44 Ecology 3 recommend that comparisons of networks should focus on relative differences rather than absolute values between the networks studied.

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10(-8). The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide ave...

Eukaryotic genome is, not only linearly but also spatially, organized into non-random architecture. Though the linear organization of genes and their epigenetic descriptors are well characterized, the relevance of their spatial organization is beginning to unfold only recently. It is increasingly being recognized that physical interactions among distant genomic elements could serve as an important mean to eukaryotic genome regulation. With the advent of proximity ligation based techniques coupled with next generation sequencing, it is now possible to explore whole genome chromatin interactions at high resolution. Emerging data on genome-wide chromatin interactions suggest that distantly located genes are not independent entities and instead cross-talk with each other in an extensive manner, supporting the notion of "chromatin interaction networks". Moreover, the data also advance the field to "3-dimensional (3D) chromatin structure and dynamics", which would enable molecular biologists to explore the spatiotemporal regulation of genome. In this article, we introduce a stepwise topological transformation of genome from 1-dimension (1D, linear) to 2dimension (2D, networks) to 3-dimension (3D, architecture) and discuss how such transformations could advance our understanding of genome biology.

In this paper, we present a novel ranking technique that we developed in the context of an application that arose in a Service Delivery setting. We consider the problem of ranking agents of a service organization. The service agents typically need to interact with other service agents to accomplish the end goal of resolving customer requests. Their ranking needs to take into account two aspects: firstly, their importance in the network structure that arises as a result of their interactions, and secondly, the value generated by the interactions involving them. We highlight several other applications which have the common theme of ranking the participants of a value creation process based on the network structure of their interactions and the value generated by their interactions. We formally present the problem and describe the modeling technique which enables us to encode the value of interaction in the graph. Our ranking algorithm is based on extension of eigen value methods. We p...

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Plants grow in communities where they interact with other plants and with other living organisms such as pollinators. On the one hand, studies of plant-plant interactions rarely consider how plants interact with other trophic levels such as pollinators. On the other, studies of plant-animal interactions rarely deal with interactions within trophic levels such as plant-plant competition and facilitation.

Background. Interspecific interactions play an important role in determining species richness and persistence in a given locality. However at some sites, the studies, especially for interaction networks on adult butterflies are scarce. The present study aimed the following objectives: (1) determine butterfly species richness and diversity that visit flowering plants, (2) compare species richness and diversity in butterfly-plant interactions among six different vegetation types and (3) analyze the structure of butterfly-flowering plant interaction networks mediated by flowers. Methods. The study was developed in six vegetation types within the natural reserve of La Mancha, located in Veracruz, Mexico. In each vegetation type, we recorded the frequency of flower visits by butterflies monthly in round plots (of radius 5 m) for 12 months. We calculated Shannon diversity for butterfly species and diversity of interactions per vegetation type. We determined the classic Jaccard similarity index among vegetation types and estimated parameters at network and species-level. Results. We found 123 species of butterflies belonging to 11 families and 87 genera. The highest number of species belonged to Hesperiidae (46 species), followed by Nymphalidae (28) and Pieridae (14). The highest butterfly diversity and interaction diversity was observed in pioneer dune vegetation (PDV), coastal dune scrub (CDS) and tropical deciduous flooding forest and wetland (TDF-W). The same order of vegetation types was found for interaction diversity. Highest species similarity was found between PDV-CDS and PDV-TDF. The butterfly-plant interaction network showed a nested structure with one module. The species Ascia monuste, Euptoieta hegesia and Leptotes cassius were the most generalist in the network, while Horama oedippus, E. hegesia, and L. cassius were the species with highest dependencies per plant species. Discussion. Our study is important because it constitutes a pioneer study of butterfly-plant interactions in this protected area, at least for adult butterflies; it shows the diversity of interactions among flowering plants and butterflies. Our research constitutes the first approach (at a community level) to explore the functional role of pollination services that butterflies provide to plant communities. We highlighted that open areas show a higher diversity and these areas shared a higher number of species that shaded sites. In the interaction networks parameters, our results highlighted the higher dependence of butterflies by the flowers on which they feed than vice versa. In conclusion, the plant species (as a feeding resource) seem to limit the presence of butterfly species. Thus, this protected area is highly relevant for Lepidoptera diversity and the interaction between these insects and flowering plants. We suggest that