Bounds on the distribution of the number of gaps when circles and lines are covered by fragments: Theory and practical application to genomic and metagenomic projects

Background  

The question of how a circle or line segment becomes covered when random arcs are marked off has arisen repeatedly in bioinformatics. The number of uncovered gaps is of particular interest. Approximate distributions for the number of gaps have been given in the literature, one motivation being ease of computation. Error bounds for these approximate distributions have not been given.     

The legacy of human use in Amazonian palm communities along environmental and accessibility gradients

Aim

Palms are iconic and dominant elements of neotropical forests. In the Amazon region, palms have been used and managed by humans for food, material, medicine and other purposes for millennia. It is, however, debated to what extent the structure of modern palm communities reflects long-term human modification. Here, we investigate the complex interplay of ecological and societal factors that influence the distributions of both human-used and non-used palms in western Amazonia.

Location

Amazonia.

Time period

Present.

Major taxa studied

Palms (Arecaceae).

Methods

We used Bayesian hierarchical joint species distribution models to predict the distributions and environmental niche dimensions of 78 western Amazonian species, and to explore their relationships with their diversity of human uses and with specific uses (food, construction and medicine). The models were parameterized with a comprehensive set of field- and satellite-derived environmental predictors.

Results

Our results suggest that a combination of ecological and anthropogenic factors drive the present-day distributions of Amazonian palms. The modelled ecological niches of the species revealed use-related species-sorting along soil, climatic, accessibility and drainage gradients. We found peaks in the proportions of useful palms and their diversity of uses in fertile soils, close to rivers, and on floodplains. These are habitats favourable for human settlement, although they harbour naturally restricted palm species pools. We also found a negative correlation between predicted palm species richness and number of human uses across western Amazonia.

Main conclusions

Soil characteristics, accessibility, and species pool size all contribute to defining palm–human relationships. At the basin scale, the signature of human use on palm communities was predicted to be stronger in the species-poor south-west than in central-western Amazonia. Overall, we conclude that environmental conditions have influenced modern Amazonian palm distributions both directly and indirectly, by regulating human settlement patterns and natural resource use over extended time periods.     

Climate or diet? The importance of biotic interactions in determining species range size

Aim

Species geographical range sizes play a crucial role in determining species vulnerability to extinction. Although several mechanisms affect range sizes, the number of biotic interactions and species climatic tolerance are often thought to play discernible roles, defining two dimensions of the Hutchinsonian niche. Yet, the relative importance of the trophic and the climatic niche for determining species range sizes is largely unknown.

Location

Central and northern Europe.

Time period

Present.

Major taxa studied

Gall-inducing sawflies and their parasitoids.

Methods

We use data documenting the spatial distributions and biotic interactions of 96 herbivore species, and their 125 parasitoids, across Europe and analyse the relationship between species range size and the climatic and trophic dimensions of the niche. We then compare the observed relationships with null expectations based on species occupancy to understand whether the relationships observed are an inevitable consequence of species range size or if they contain information about the importance of each dimension of the niche on species range size.

Results

We find that both niche dimensions are positively correlated with species range size, with larger ranges being associated with wider climatic tolerances and larger numbers of interactions. However, diet breadth appears to more strongly limit species range size. Species with larger ranges have more interactions locally and they are also able to interact with a larger diversity of species across sites (i.e. higher β-diversity), resulting in a larger number of interactions at continental scales.

Main conclusions

We show for the first time how different aspects of species diet niches are related to their range size. Our study offers new insight into the importance of biotic interactions in determining species spatial distributions, which is critical for improving understanding and predictions of species vulnerability to extinction under the current rates of global environmental change.     

Evaluation and classification of RING-finger domains encoded by the <Emphasis Type="Italic">Arabidopsis</Emphasis> genome

Background

In computational analysis, the RING-finger domain is one of the most frequently detected domains in the Arabidopsis proteome. In fact, it is more abundant in Arabidopsis than in other eukaryotic genomes. However, computational analysis might classify ambiguous domains of the closely related PHD and LIM motifs as RING domains by mistake. Thus, we set out to define an ordered set of Arabidopsis RING domains by evaluating predicted domains on the basis of recent structural data.

Results

Inspection of the proteome with a current InterPro release predicts 446 RING domains. We evaluated each detected domain and as a result eliminated 59 false positives. The remaining 387 domains were grouped by cluster analysis and according to their metal-ligand arrangement. We further defined novel patterns for additional computational analyses of the proteome. They were based on recent structural data that enable discrimination between the related RING, PHD and LIM domains. These patterns allow us to predict with different degrees of certainty whether a particular domain is indeed likely to form a RING finger.

Conclusions

In summary, 387 domains have a significant potential to form a RING-type cross-brace structure. Many of these RING domains overlap with predicted PHD domains; however, the RING domain signature mostly prevails. Thus, the abundance of PHD domains in Arabidopsis has been significantly overestimated. Cluster analysis of the RING domains defines groups of proteins, which frequently show significant similarity outside the RING domain. These groups document a common evolutionary origin of their members and potentially represent genes of overlapping functionality.

     

A Systematic Survey of Mini-Proteins in Bacteria and Archaea

Background

Mini-proteins, defined as polypeptides containing no more than 100 amino acids, are ubiquitous in prokaryotes and eukaryotes. They play significant roles in various biological processes, and their regulatory functions gradually attract the attentions of scientists. However, the functions of the majority of mini-proteins are still largely unknown due to the constraints of experimental methods and bioinformatic analysis.

Methodology/Principal Findings

In this article, we extracted a total of 180,879 mini-proteins from the annotations of 532 sequenced genomes, including 491 strains of Bacteria and 41 strains of Archaea. The average proportion of mini-proteins among all genomic proteins is approximately 10.99%, but different strains exhibit remarkable fluctuations. These mini-proteins display two notable characteristics. First, the majority are species-specific proteins with an average proportion of 58.79% among six representative phyla. Second, an even larger proportion (70.03% among all strains) is hypothetical proteins. However, a fraction of highly conserved hypothetical proteins potentially play crucial roles in organisms. Among mini-proteins with known functions, it seems that regulatory and metabolic proteins are more abundant than essential structural proteins. Furthermore, domains in mini-proteins seem to have greater distributions in Bacteria than Eukarya. Analysis of the evolutionary progression of these domains reveals that they have diverged to new patterns from a single ancestor.

Conclusions/Significance

Mini-proteins are ubiquitous in bacterial and archaeal species and play significant roles in various functions. The number of mini-proteins in each genome displays remarkable fluctuation, likely resulting from the differential selective pressures that reflect the respective life-styles of the organisms. The answers to many questions surrounding mini-proteins remain elusive and need to be resolved experimentally.     

Biogeography of Human Infectious Diseases: A Global Historical Analysis

Objectives

Human pathogen richness and prevalence vary widely across the globe, yet we know little about whether global patterns found in other taxa also predict diversity in this important group of organisms. This study (a) assesses the relative importance of temperature, precipitation, habitat diversity, and population density on the global distributions of human pathogens and (b) evaluates the species-area predictions of island biogeography for human pathogen distributions on oceanic islands.

Methods

Historical data were used in order to minimize the influence of differential access to modern health care on pathogen prevalence. The database includes coded data (pathogen, environmental and cultural) for a worldwide sample of 186 non-industrial cultures, including 37 on islands. Prevalence levels for 10 pathogens were combined into a pathogen prevalence index, and OLS regression was used to model the environmental determinants of the prevalence index and number of pathogens.

Results

Pathogens (number and prevalence index) showed the expected latitudinal gradient, but predictors varied by latitude. Pathogens increased with temperature in high-latitude zones, while mean annual precipitation was a more important predictor in low-latitude zones. Other environmental factors associated with more pathogens included seasonal dry extremes, frost-free climates, and human population density outside the tropics. Islands showed the expected species-area relationship for all but the smallest islands, and the relationship was not mediated by habitat diversity. Although geographic distributions of free-living and parasitic taxa typically have different determinants, these data show that variables that influence the distribution of free-living organisms also shape the global distribution of human pathogens. Understanding the cause of these distributions is potentially important, since geographical variation in human pathogens has an important influence on global disparities in human welfare.     

A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks

Background:  

Receptors and scaffold proteins possess a number of distinct domains and bind multiple partners. A common problem in modeling signaling systems arises from a combinatorial explosion of different states generated by feasible molecular species. The number of possible species grows exponentially with the number of different docking sites and can easily reach several millions. Models accounting for this combinatorial variety become impractical for many applications.     

Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

Background

Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information.

Results

AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins.

Conclusion

AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains.     

Higher spring temperatures increase food scarcity and limit the current and future distributions of crossbills

Aim

Understanding how climate affects species distributions remains a major challenge, with the relative importance of direct physiological effects versus biotic interactions still poorly understood. We focus on three species of resource specialists (crossbill Loxia finches) to assess the role of climate in determining the seasonal availability of their food, the importance of climate and the occurrence of their food plants for explaining their current distributions, and to predict changes in their distributions under future climate change scenarios.

Location

Europe.

Methods

We used datasets on the timing of seed fall in European Scots pine Pinus sylvestris forests (where different crossbill species occur) to estimate seed fall phenology and climate data to determine its influence on spatial and temporal variation in the timing of seed fall to provide a link between climate and seed scarcity for crossbills. We used large‐scale datasets on crossbill distribution, cover of the conifers relied on by the three crossbill species and climate variables associated with timing of seed fall, to assess their relative importance for predicting crossbill distributions. We used species distribution modelling to predict changes in their distributions under climate change projections for 2070.

Results

We found that seed fall occurred 1.5–2 months earlier in southern Europe than in Sweden and Scotland and was associated with variation in spring maximum temperatures and precipitation. These climate variables and area covered with conifers relied on by the crossbills explained much of their observed distributions. Projections under global change scenarios revealed reductions in potential crossbill distributions, especially for parrot crossbills.

Main conclusions

Ranges of resource specialists are directly influenced by the presence of their food plants, with climate conditions further affecting resource availability and the window of food scarcity indirectly. Future distributions will be determined by tree responses to changing climatic conditions and the impact of climate on seed fall phenology.

     

Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis

Background

The distribution of chromatin-associated proteins plays a key role in directing nuclear function. Previously, we developed an image-based method to quantify the nuclear distributions of proteins and showed that these distributions depended on the phenotype of human mammary epithelial cells. Here we describe a method that creates a hierarchical tree of the given cell phenotypes and calculates the statistical significance between them, based on the clustering analysis of nuclear protein distributions.

Results

Nuclear distributions of nuclear mitotic apparatus protein were previously obtained for non-neoplastic S1 and malignant T4-2 human mammary epithelial cells cultured for up to 12 days. Cell phenotype was defined as S1 or T4-2 and the number of days in cultured. A probabilistic ensemble approach was used to define a set of consensus clusters from the results of multiple traditional cluster analysis techniques applied to the nuclear distribution data. Cluster histograms were constructed to show how cells in any one phenotype were distributed across the consensus clusters. Grouping various phenotypes allowed us to build phenotype trees and calculate the statistical difference between each group. The results showed that non-neoplastic S1 cells could be distinguished from malignant T4-2 cells with 94.19% accuracy; that proliferating S1 cells could be distinguished from differentiated S1 cells with 92.86% accuracy; and showed no significant difference between the various phenotypes of T4-2 cells corresponding to increasing tumor sizes.

Conclusion

This work presents a cluster analysis method that can identify significant cell phenotypes, based on the nuclear distribution of specific proteins, with high accuracy.

     

A hybrid parameter estimation algorithm for beta mixtures and applications to methylation state classification

Background

Mixtures of beta distributions are a flexible tool for modeling data with values on the unit interval, such as methylation levels. However, maximum likelihood parameter estimation with beta distributions suffers from problems because of singularities in the log-likelihood function if some observations take the values 0 or 1.

Methods

While ad-hoc corrections have been proposed to mitigate this problem, we propose a different approach to parameter estimation for beta mixtures where such problems do not arise in the first place. Our algorithm combines latent variables with the method of moments instead of maximum likelihood, which has computational advantages over the popular EM algorithm.

Results

As an application, we demonstrate that methylation state classification is more accurate when using adaptive thresholds from beta mixtures than non-adaptive thresholds on observed methylation levels. We also demonstrate that we can accurately infer the number of mixture components.

Conclusions

The hybrid algorithm between likelihood-based component un-mixing and moment-based parameter estimation is a robust and efficient method for beta mixture estimation. We provide an implementation of the method (“betamix”) as open source software under the MIT license.

     

Birth and death of protein domains: A simple model of evolution explains power law behavior

Background  

Power distributions appear in numerous biological, physical and other contexts, which appear to be fundamentally different. In biology, power laws have been claimed to describe the distributions of the connections of enzymes and metabolites in metabolic networks, the number of interactions partners of a given protein, the number of members in paralogous families, and other quantities. In network analysis, power laws imply evolution of the network with preferential attachment, i.e. a greater likelihood of nodes being added to pre-existing hubs. Exploration of different types of evolutionary models in an attempt to determine which of them lead to power law distributions has the potential of revealing non-trivial aspects of genome evolution.     

Longitudinal study of Plasmodium falciparum and Plasmodium vivax in a Karen population in Thailand

Background

Pregnancy malaria is caused by Plasmodium falciparum -infected erythrocytes binding the placental receptor chondroitin sulfate A (CSA). This results in accumulation of parasites in the placenta with severe clinical consequences for the mother and her unborn child. Women become resistant to placental malaria as antibodies are acquired which specifically target the surface of infected erythrocytes binding in the placenta. VAR2CSA is most likely the parasite-encoded protein which mediates binding to the placental receptor CSA. Several domains have been shown to bind CSA in vitro; and it is apparent that a VAR2CSA-based vaccine cannot accommodate all the CSA binding domains and serovariants. It is thus of high priority to define minimal ligand binding regions throughout the VAR2CSA molecule.

Methods

To define minimal CSA-binding regions/peptides of VAR2CSA, a phage display library based on the entire var2csa coding region was constructed. This library was screened on immobilized CSA and cells expressing CSA resulting in a limited number of CSA-binding phages. Antibodies against these peptides were affinity purified and tested for reactivity against CSA-binding infected erythrocytes.

Results

The most frequently identified phages expressed peptides residing in the parts of VAR2CSA previously defined as CSA binding. In addition, most of the binding regions mapped to surface-exposed parts of VAR2CSA. The binding of a DBL2X peptide to CSA was confirmed with a synthetic peptide. Antibodies against a CSA-binding DBL2X peptide reacted with the surface of infected erythrocytes indicating that this epitope is accessible for antibodies on native VAR2CSA on infected erythrocytes.

Conclusion

Short continuous regions of VAR2CSA with affinity for multiple types of CSA were defined. A number of these regions localize to CSA-binding domains and to surface-exposed regions within these domains and a synthetic peptide corresponding to a peptide sequence in DBL2 was shown to bind to CSA and not to CSC. It is likely that some of these epitopes are involved in native parasite CSA adhesion. However, antibodies directed against single epitopes did not inhibit parasite adhesion. This study supports phage display as a technique to identify CSA-binding regions of large proteins such as VAR2CSA.     

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

Background

The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity.

Scope

This review summarizes empirical evidence for factors that determine palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts of these factors and the scale at which they function is discussed. Finally a hierarchical scale framework is developed to guide predictor selection for future studies.

Conclusions

Determinants of palm distributions, composition and richness vary with spatial scale. For species distributions, climate appears to be important at landscape and broader scales, soil, topography and vegetation at landscape and local scales, hydrology at local scales, and dispersal at all scales. For community composition, soil appears important at regional and finer scales, hydrology, topography and vegetation at landscape and local scales, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e.g. climate on regional to finer scales, and hydrology and topography on landscape and broader scales. The importance of biotic interactions – apart from general vegetation structure effects – for the geographic ecology of palms is generally underexplored. Future studies should target scale–predictor combinations and geographic domains not studied yet. To avoid biased inference, one should ideally include at least all predictors previously found important at the spatial scale of investigation.     

Inclusion of the glucocorticoid receptor in a hypothalamic pituitary adrenal axis model reveals bistability

Background

This article deals with the theoretical size distribution (of number of sub-taxa) of a fossil taxon arising from a simple null model of macroevolution.

Model

New species arise through speciations occurring independently and at random at a fixed probability rate, while extinctions either occur independently and at random (background extinctions) or cataclysmically. In addition new genera are assumed to arise through speciations of a very radical nature, again assumed to occur independently and at random at a fixed probability rate.

Conclusion

The size distributions of the pioneering genus (following a cataclysm) and of derived genera are determined. Also the distribution of the number of genera is considered along with a comparison of the probability of a monospecific genus with that of a monogeneric family.     

The molecular phylogeny of eph receptors and ephrin ligands

Background  

The tissue distributions and functions of Eph receptors and their ephrin ligands have been well studied, however less is known about their evolutionary history. We have undertaken a phylogenetic analysis of Eph receptors and ephrins from a number of invertebrate and vertebrate species.     

Constructing Hypothetical Risk Data from the Area under the ROC Curve: Modelling Distributions of Polygenic Risk

Background

Modeling studies using hypothetical polygenic risk data can be an efficient tool for investigating the effectiveness of downstream applications such as targeting interventions to risk groups to justify whether empirical investigation is warranted. We investigated the assumptions underlying a method that simulates risk data for specific values of the area under the receiver operating characteristic curve (AUC).

Methods

The simulation method constructs risk data for a hypothetical population based on the population disease risk, and the odds ratios and frequencies of genetic variants. By systematically varying the parameters, we investigated under what conditions AUC values represent unique ROC curves with unique risk distributions for patients and nonpatients, and to what extend risk data can be simulated for precise values of the AUC.

Results

Using larger number of genetic variants each with a modest effect, we observed that the distributions of estimated risks of patients and nonpatients were similar for various combinations of the odds ratios and frequencies of the risk alleles. Simulated ROC curves overlapped empirical curves with the same AUC.

Conclusions

Polygenic risk data can be effectively and efficiently created using a simulation method. This allows to further investigate the potential applications of stratifying interventions on the basis of polygenic risk.     

Malaria knowledge and agricultural practices that promote mosquito breeding in two rural farming communities in Oyo State, Nigeria

Background

Malaria caused by Plasmodium falciparum can result in several different syndromes with severe clinical consequences for the about 200 million individuals infected each year. During pregnancy, women living in endemic areas become susceptible to malaria due to lack of antibodies against a unique P. falciparum membrane protein, named VAR2CSA. This antigen is not expressed in childhood infections, since it binds chondroitin sulphate A (CSA) expressed on the intervillous space in the placenta. A vaccine appears possible because women acquire protective antibodies hindering sequestration in the placenta as a function of parity. A challenge for vaccine development is to design small constructs of this large antigen, which can induce broadly protective antibodies. It has previously been shown that one domain of VAR2CSA, DBL4-FCR3, induces parasite adhesion-blocking antibodies. In this study, it is demonstrated that other domains of VAR2CSA also can induce antibodies with inhibitory activity.

Methods

All VAR2CSA domains from the 3D7 and HB3 parasites were produced in Baculovirus-transfected insect cells. Groups of three rats per protein were immunized and anti-sera were tested for surface reactivity against infected erythrocytes expressing FCR3 VAR2CSA and for the ability to inhibit FCR3CSA parasite adhesion to CSA. The fine specificity of the immune sera was analysed by VAR2CSA peptide arrays.

Results

Inhibitory antibodies were induced by immunization with DBL3-HB3 T1 and DBL1-3D7. However, unlike the previously characterised DBL4-FCR3 response the inhibitory response against DBL1-3D7 and DBL3-HB3 T1 was poorly reproduced in the second rounds of immunizations.

Conclusion

It is possible to induce parasite adhesion-blocking antibodies when immunizing with a number of different VAR2CSA domains. This indicates that the CSA binding site in VAR2CSA is comprised of epitopes from different domains.     

The Nonsteroidal Anti-Inflammatory Drug Indomethacin Induces Heterogeneity in Lipid Membranes: Potential Implication for Its Diverse Biological Action

Background

The nonsteroidal anti-inflammatory drug (NSAID), indomethacin (Indo), has a large number of divergent biological effects, the molecular mechanism(s) for which have yet to be fully elucidated. Interestingly, Indo is highly amphiphilic and associates strongly with lipid membranes, which influence localization, structure and function of membrane-associating proteins and actively regulate cell signaling events. Thus, it is possible that Indo regulates diverse cell functions by altering micro-environments within the membrane. Here we explored the effect of Indo on the nature of the segregated domains in a mixed model membrane composed of dipalmitoyl phosphatidyl-choline (di16∶0 PC, or DPPC) and dioleoyl phosphatidyl-choline (di18∶1 PC or DOPC) and cholesterol that mimics biomembranes.

Methodology/Principal Findings

Using a series of fluorescent probes in a fluorescence resonance energy transfer (FRET) study, we found that Indo induced separation between gel domains and fluid domains in the mixed model membrane, possibly by enhancing the formation of gel-phase domains. This effect originated from the ability of Indo to specifically target the ordered domains in the mixed membrane. These findings were further confirmed by measuring the ability of Indo to affect the fluidity-dependent fluorescence quenching and the level of detergent resistance of membranes.

Conclusion/Significance

Because the tested lipids are the main lipid constituents in cell membranes, the observed formation of gel phase domains induced by Indo potentially occurs in biomembranes. This marked Indo-induced change in phase behavior potentially alters membrane protein functions, which contribute to the wide variety of biological activities of Indo and other NSAIDs.