Predicting trophic relations in ecological networks: A test of the Allometric Diet Breadth Model

Few food web theory hypotheses/predictions can be readily tested using likelihoods of reproducing the data. Simple probabilistic models for food web structure, however, are an exception as their likelihoods were recently derived. Here I test the performance of a more complex model for food web structure that is grounded in the allometric scaling of interactions with body size and the theory of optimal foraging (Allometric Diet Breadth Model—ADBM). This deterministic model has been evaluated by measuring the fraction of trophic relations it correctly predicts. I contrasted this value with that produced by simpler models based on body sizes and found that the quantitative information on allometric scaling and optimal foraging does not significantly increase model fit. Also, I present a method to compute the p-value for the fraction of trophic interactions correctly predicted by the ADBM, or any other model, with respect to three probabilistic models. I find that the ADBM predicts significantly more links than random graphs, but other models can outperform it. Although optimal foraging and allometric scaling may improve our understanding of food webs, the ADBM needs to be modified or replaced to find support in the data.     

Direct measurement of protein osmotic second virial cross coefficients by cross-interaction chromatography

The importance of weak protein interactions, such as protein self-association, is widely recognized in a variety of biological and technological processes. Although protein self-association has been studied extensively, much less attention has been devoted to weak protein cross-association, mainly due to the difficulties in measuring weak interactions between different proteins in solution. Here a framework is presented for quantifying the osmotic second virial cross coefficient directly using a modified form of self-interaction chromatography called cross-interaction chromatography. A theoretical relationship is developed between the virial cross coefficient and the chromatographic retention using statistical mechanics. Measurements of bovine serum albumin (BSA)/lysozyme cross-association using cross-interaction chromatography agree well with the few osmometry measurements available in the literature. Lysozyme/alpha-chymotrypsinogen interactions were also measured over a wide range of solution conditions, and some counterintuitive trends were observed that may provide new insight into the molecular origins of weak protein interactions. The virial cross coefficients presented in this work may also provide insight into separation processes that are influenced by protein cross-interactions, such as crystallization, precipitation, and ultrafiltration.     

Collision induced spatial organization of microtubules

The dynamic behavior of microtubules in solution can be strongly modified by interactions with walls or other structures. We examine here a microtubule growth model where the increase in size of the plus-end is perturbed by collisions with other microtubules. We show that such a simple mechanism of constrained growth can induce ordered structures and patterns from an initially isotropic and homogeneous suspension. We find that microtubules self-organize locally in randomly oriented domains that grow and compete with each other. A weak orientation bias, similar to the one induced by gravity or cellular boundaries is enough to influence the domain growth direction, eventually leading to a macroscopic sample orientation.     

Climate change and multitrophic interactions in soil: the primacy of plants and functional domains

Soil multitrophic interactions transfer energy from plants as the predominant primary producer to communities of organisms that occupy different positions in the food chain and are linked by multiple ecological networks, which is the soil food web. Soil food web sequesters carbon, cycles nutrients, maintains soil health to suppress pathogens, helps plants tolerate abiotic and biotic stress, and maintains ecosystem resilience and sustainability. Understanding the influence of climate change on soil multitrophic interactions is necessary to maintain these essential ecosystem services. But summarising this influence is a daunting task due to a paucity of knowledge and a lack of clarity on the ecological networks that constitute these interactions. The scant literature is fragmented along disciplinary lines, often reporting inconsistent findings that are context and scale‐dependent. We argue for the differentiation of soil multitrophic interactions along functional and spatial domains to capture cross‐disciplinary knowledge and mechanistically link all ecological networks to reproduce full functionalities of the soil food web. Distinct from litter mediated interactions in detritosphere or elsewhere in the soil, the proposed ‘pathogen suppression’ and ‘stress tolerance’ interactions operate in the rhizosphere. A review of the literature suggests that climate change will influence the relative importance, frequency and composition of functional groups, their trophic interactions and processes controlling these interactions. Specific climate change factors generally have a beneficial influence on pathogen suppression and stress tolerance, but findings on the overall soil food web are inconsistent due to a high level of uncertainty. In addition to an overall improvement in the understanding of soil multitrophic interactions using empirical and modelling approaches, we recommend linking biodiversity to function, understanding influence of combinations of climatic factors on multitrophic interactions and the evolutionary ecology of multitrophic interactions in a changing climate as areas that deserve most attention.     

Predicting P-glycoprotein-mediated drug transport based on support vector machine and three-dimensional crystal structure of P-glycoprotein

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening.     

Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

Background

While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well.

Results

We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly.Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation.

Conclusion

Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions by utilizing expectation scores of single domain interactions.

     

Food Web Assembly at the Landscape Scale: Using Stable Isotopes to Reveal Changes in Trophic Structure During Succession

Food webs are increasingly evaluated at the landscape scale, accounting for spatial interactions involving different nutrient and energy channels. Also, while long viewed as static, food webs are increasingly seen as dynamic entities that assemble during vegetation succession. The next necessary step is, therefore, to link nutrient flows between ecosystems to local food web assembly processes. In this study, we used a 100-year salt marsh succession in which we investigated the long-term changes in food web organization, especially focusing on the balance between internal versus external nutrient sources. We found that during food web assembly, the importance of internal (terrestrial) nutrient cycling increases at the expense of external (marine) inputs. This change from external to internal nutrient cycling is associated with strong shifts in the basis of energy channels within the food web. In early succession, detritivores are mostly fuelled by marine inputs whereas in later succession they thrive on locally produced plant litter, with consequences for their carnivores. We conclude that this 100 years of food web assembly proceeds by gradual decoupling of terrestrial nutrient cycling from the marine environment, and by associated rearrangements in the herbivore and detritivore energy channels. Food web assembly thus interacts with nutrient and energy flows across ecosystem boundaries.     

Caught in the web: Spider web architecture affects prey specialization and spider–prey stoichiometric relationships

Quantitative approaches to predator–prey interactions are central to understanding the structure of food webs and their dynamics. Different predatory strategies may influence the occurrence and strength of trophic interactions likely affecting the rates and magnitudes of energy and nutrient transfer between trophic levels and stoichiometry of predator–prey interactions. Here, we used spider–prey interactions as a model system to investigate whether different spider web architectures—orb, tangle, and sheet‐tangle—affect the composition and diet breadth of spiders and whether these, in turn, influence stoichiometric relationships between spiders and their prey. Our results showed that web architecture partially affects the richness and composition of the prey captured by spiders. Tangle‐web spiders were specialists, capturing a restricted subset of the prey community (primarily Diptera), whereas orb and sheet‐tangle web spiders were generalists, capturing a broader range of prey types. We also observed elemental imbalances between spiders and their prey. In general, spiders had higher requirements for both nitrogen (N) and phosphorus (P) than those provided by their prey even after accounting for prey biomass. Larger P imbalances for tangle‐web spiders than for orb and sheet‐tangle web spiders suggest that trophic specialization may impose strong elemental constraints for these predators unless they display behavioral or physiological mechanisms to cope with nutrient limitation. Our findings suggest that integrating quantitative analysis of species interactions with elemental stoichiometry can help to better understand the occurrence of stoichiometric imbalances in predator–prey interactions.     

A landscape theory for food web architecture

Ecologists have long searched for structures and processes that impart stability in nature. In particular, food web ecology has held promise in tackling this issue. Empirical patterns in food webs have consistently shown that the distributions of species and interactions in nature are more likely to be stable than randomly constructed systems with the same number of species and interactions. Food web ecology still faces two fundamental challenges, however. First, the quantity and quality of food web data required to document both the species richness and the interaction strengths among all species within food webs is largely prohibitive. Second, where food webs have been well documented, spatial and temporal variation in food web structure has been ignored. Conversely, research that has addressed spatial and temporal variation in ecosystems has generally ignored the full complexity of food web architecture. Here, we incorporate empirical patterns, largely from macroecology and behavioural ecology, into a spatially implicit food web structure to construct a simple landscape theory of food web architecture. Such an approach both captures important architectural features of food webs and allows for an exploration of food web structure across a range of spatial scales. Finally, we demonstrated that food webs are hierarchically organized along the spatial and temporal niche axes of species and their utilization of food resources in ways that stabilize ecosystems.     

Dimensional analysis in mathematical biology. II

The application of dimensional analysis in biology is further illustrated by functional equations composed of dimensionless numbers and dealing with renal physiology, lung physiology and plant leaf shape. Dimensional variables and dimensionless numbers are examined from the viewpoint of numerical invariant properties of a certain physical system. Utilization of the method for problems such as design of an artificial kidney is considered briefly. A tabulation of variables useful in biology is given, with suggestions for a number of new dimensional entities. A continuation of the list of dimensionless invariants from Part I (Bull. Math. Biophysics,23, 355–376, 1961) is provided and includes terms pertaining to general physiology, geometric growth, metabolism, ecological interactions, muscle kinetics and other areas. It is pointed out that use of dimensionless ratios (similarity criteria) makes possible a direct comparison of form or shape factors and relative growth ratios with a variety of physical ratios, through the use of functional equations containing only dimensionless entities. Organismal similarity during growth and development, and between genetically related species, may be analyzed in terms of “automodel” or “self-similar” systems governed by certain dimensionless invariants. Tables of biological variables and dimensionless groupings are included.     

Identification of peptide‐binding sites within BSA using rapid,laser‐induced covalent cross‐linking combined with high‐performance mass spectrometry

We are developing a rapid, time‐resolved method using laser‐activated cross‐linking to capture protein‐peptide interactions as a means to interrogate the interaction of serum proteins as delivery systems for peptides and other molecules. A model system was established to investigate the interactions between bovine serum albumin (BSA) and 2 peptides, the tridecapeptide budding‐yeast mating pheromone (α‐factor) and the decapeptide human gonadotropin‐releasing hormone (GnRH). Cross‐linking of α‐factor, using a biotinylated, photoactivatable p‐benzoyl‐L‐phenylalanine (Bpa)–modified analog, was energy‐dependent and achieved within seconds of laser irradiation. Protein blotting with an avidin probe was used to detect biotinylated species in the BSA‐peptide complex. The cross‐linked complex was trypsinized and then interrogated with nano‐LC–MS/MS to identify the peptide cross‐links. Cross‐linking was greatly facilitated by Bpa in the peptide, but some cross‐linking occurred at higher laser powers and high concentrations of a non‐Bpa–modified α‐factor. This was supported by experiments using GnRH, a peptide with sequence homology to α‐factor, which was likewise found to be cross‐linked to BSA by laser irradiation. Analysis of peptides in the mass spectra showed that the binding site for both α‐factor and GnRH was in the BSA pocket defined previously as the site for fatty acid binding. This model system validates the use of laser‐activation to facilitate cross‐linking of Bpa‐containing molecules to proteins. The rapid cross‐linking procedure and high performance of MS/MS to identify cross‐links provides a method to interrogate protein‐peptide interactions in a living cell in a time‐resolved manner.     

Indirect food web interactions increase growth of an algivorous stream fish

1. We tested the hypothesis that indirect food web interactions between some common, invertivorous fishes and their prey would positively affect growth of an algivorous fish species. Specifically, we predicted that orangethroat darter (Etheostoma spectabile) would increase periphyton biomass via a top‐down pathway, indirectly enhancing growth of the algivorous central stoneroller minnow (Campostoma anomalum). Moreover, we predicted that sand shiner (Notropis stramineus) would increase periphyton biomass via a bottom‐up pathway and indirectly enhance growth of the stoneroller minnow. 2. In an 83‐day experiment in large, outdoor, stream mesocosms, we stocked two fish species per mesocosm (stoneroller and either darter or shiner), estimated the effects of the invertivorous and grazing fishes on periphyton biomass and estimated growth of the algivorous fish. 3. The darter consumed grazing invertebrates, indirectly increasing periphyton biomass. The shiner consumed terrestrial insects as predicted, but it did not affect periphyton biomass. 4. In support of our hypothesis, the darter indirectly enhanced stoneroller growth. As predicted, stonerollers consumed the increased periphyton in streams with darters, resulting in greater growth, condition and gut fullness compared to streams without darters. No indirect interaction was observed between stonerollers and shiners. 5. Our study suggests that some invertivorous fish species can positively affect growth of algivorous fishes through indirect food web interactions. Thus, in stream communities, it is possible that the loss of a single, invertivorous fish taxon could have negative consequences on algivorous fish populations via the removal of positive indirect food web interactions.     

Spatial stoichiometry: cross‐ecosystem material flows and their impact on recipient ecosystems and organisms

Cross‐ecosystem material flows, in the form of inorganic nutrients, detritus and organisms, spatially connect ecosystems and impact food web dynamics. To date research on material flows has focused on the impact of the quantity of these flows and largely ignored their elemental composition, or quality. However, the ratios of elements like carbon, nitrogen and phosphorus can influence the impact material flows have on food web interactions through stoichiometric mismatches between resources and consumers. The type and movement of materials likely vary in their ability to change stoichiometric constraints within the recipient ecosystem and materials may undergo changes in their own stoichiometry during transport. In this literature review we evaluate the importance of cross‐ecosystem material flows within the framework of ecological stoichiometry. We explore how movement in space and time impacts the stoichiometry of material flow, as these transformations are essential to consider when assessing the ability of these flows to impact food web productivity and ecosystem functioning. Our review suggests that stoichiometry of cross‐ecosystem material flows are highly dynamic and undergo changes during transport across the landscape or from human influence. These material flows can impact recipient organisms if they change stoichiometry of the abiotic medium, or provide resources that have a different stoichiometry to in situ resources. They might also alter consumer excretion rates, in turn altering the availability of nutrients in the recipient ecosystem. These alterations in stoichiometric constraints of recipient organisms can have cascading trophic effects and shape food web dynamics. We highlight significant gaps in the literature and suggest new avenues for research that explore how cross‐ecosystem material flows impact recipient ecosystems when considering differences in stoichiometric quality, their movement through the landscape and across ecosystem boundaries, and the nutritional constraints of the recipient organisms.     

Autochthonous or allochthonous resources determine the characteristic population dynamics of ecosystem engineers and their impacts

Ecosystem engineering, or the modification of physical environments by organisms, can influence trophic interactions and thus food web dynamics. Although existing theory exclusively considers engineers using autochthonous resources, many empirical studies show that they often depend on allochthonous resources. By developing a simple mathematical model involving an ecosystem engineer that modifies the physical environment through its activities, its resource, and physical environment modified by the engineer, we compare the effects of autochthonous and allochthonous resources on the dynamics and stability of community with ecosystem engineers. To represent a variety of real situations, we consider engineers that alter either resource productivity, engineer feeding rate on the resource, or engineer mortality, and incorporate time-lagged responses of the physical environment. Our model shows that the effects of ecosystem engineering on community dynamics depend greatly on resource types. When the engineer consumes autochthonous resources, the community can exhibit oscillatory dynamics if the engineered environment affects engineer’s feeding rate or mortality. These cyclic behaviors are, however, stabilized by a slowly responding physical environment. When allochthonous resources are supplied as donor-controlled, on the other hand, the engineer population is unlikely to oscillate but instead can undergo unbounded growth if the engineered environment affects resource productivity or engineer mortality. This finding suggests that ecosystem engineers utilizing allochthonous resources may be more likely to reach high abundance and cause strong impacts on ecosystems. Our results highlight that community-based, compounding effects of trophic and physical biotic interactions of ecosystem engineers depend crucially on whether the engineers utilize autochthonous or allochthonous resources.     

Specificity in protein-DNA interactions: energetic recognition by the (cytosine-C5)-methyltransferase from HhaI

Sequence-specific interactions between proteins and DNA are essential for a variety of biological functions. The (cytosine-C5)-methyltransferase from HhaI (M.HhaI) specifically modifies the second base in GCGC sequences, employing a base flipping mechanism to access the target base being chemically modified. The mechanism of sequence-specific recognition of M.HhaI is not evident based on crystallographic structures, leading to the suggestion that recognition is linked to the flipping event itself, a process that may be referred to as energetic recognition. Using computational methods, it is shown that the free energy barriers to flipping are significantly higher in non-cognate versus the cognate sequence, supporting the energetic recognition mechanism. Energetic recognition is imparted by two protein "selectivity filters" that function via a "web" of protein-DNA interactions in short-lived, high energy states present along the base flipping pathway. Other sequence-specific DNA binding proteins whose function involves significant distortion of DNA's conformation may use a similar recognition mechanism.     

Food web structure and interaction strength pave the way for vulnerability to extinction

This paper focuses on how food web structure and interactions among species affects the vulnerability, due to environmental variability, to extinction of species at different positions in model food webs. Vulnerability is here not measured by a traditional extinction threshold but is instead inspired by the IUCN criteria for endangered species: an observed rapid decline in population abundance. Using model webs influenced by stochasticity with zero autocorrelation, we investigate the ecological determinants of species vulnerability, i.e. the trophic interactions between species and food web structure and how these interact with the risk of sudden drops in abundance of species. We find that (i) producers fulfil the criterion of vulnerable species more frequently than other species, (ii) food web structure is related to vulnerability, and (iii) the vulnerability of species is greater when involved in a strong trophic interaction than when not. We note that our result on the relationship between extinction risk and trophic position of species contradict previous suggestions and argue that the main reason for the discrepancy probably is due to the fact that we study the vulnerability to environmental stochasticity and not extinction risk due to overexploitation, habitat destruction or interactions with introduced species. Thus, we suggest that the vulnerability of species to environmental stochasticity may be differently related to trophic position than the vulnerability of species to other factors. Earlier research on species extinctions has looked for intrinsic traits of species that correlate with increased vulnerability to extinction. However, to fully understand the extinction process we must also consider that species interactions may affect vulnerability and that not all extinctions are the result of long, gradual reductions in species abundances. Under environmental stochasticity (which importance frequently is assumed to increase as a result of climate change) and direct and indirect interactions with other species some extinctions may occur rapidly and apparently unexpectedly. To identify the first declines of population abundances that may escalate and lead to extinctions as early as possible, we need to recognize which species are at greatest risk of entering such dangerous routes and under what circumstances. This new perspective may contribute to our understanding of the processes leading to extinction of populations and eventually species. This is especially urgent in the light of the current biodiversity crisis where a large fraction of the world's biodiversity is threatened.     

Towards a processual microbial ontology

Standard microbial evolutionary ontology is organized according to a nested hierarchy of entities at various levels of biological organization. It typically detects and defines these entities in relation to the most stable aspects of evolutionary processes, by identifying lineages evolving by a process of vertical inheritance from an ancestral entity. However, recent advances in microbiology indicate that such an ontology has important limitations. The various dynamics detected within microbiological systems reveal that a focus on the most stable entities (or features of entities) over time inevitably underestimates the extent and nature of microbial diversity. These dynamics are not the outcome of the process of vertical descent alone. Other processes, often involving causal interactions between entities from distinct levels of biological organisation, or operating at different time scales, are responsible not only for the destabilisation of pre-existing entities, but also for the emergence and stabilisation of novel entities in the microbial world. In this article we consider microbial entities as more or less stabilised functional wholes, and sketch a network-based ontology that can represent a diverse set of processes including, for example, as well as phylogenetic relations, interactions that stabilise or destabilise the interacting entities, spatial relations, ecological connections, and genetic exchanges. We use this pluralistic framework for evaluating (i) the existing ontological assumptions in evolution (e.g. whether currently recognized entities are adequate for understanding the causes of change and stabilisation in the microbial world), and (ii) for identifying hidden ontological kinds, essentially invisible from within a more limited perspective. We propose to recognize additional classes of entities that provide new insights into the structure of the microbial world, namely “processually equivalent” entities, “processually versatile” entities, and “stabilized” entities.     

Tree Species Richness Strengthens Relationships between Ants and the Functional Composition of Spider Assemblages in a Highly Diverse Forest

In species‐rich ecosystems, such as subtropical and tropical forests, higher trophic level interactions are key mediators of ecosystem functioning. Plant species loss may alter these interactions, but the effects of plant diversity might be modified by intraguild interactions, particularly among predators. We analyzed the relationships between spiders and ants, two dominant predatory arthropod taxa, on tree saplings across a gradient from medium to high woody plant species richness in a subtropical forest in Southeast China. Neither ant nor spider total biomass was significantly related to plant species richness. By contrast, the biomass distribution of web‐building and hunting spiders changed and spider family richness increased in the presence of ants, resulting in more web builder‐dominated assemblages. However, these relationships depended on the plant communities, and were stronger in plots with higher plant species richness. Our results indicate that in addition to potential effects of ants on hunting spiders in particular, ants could indirectly influence intraguild interactions within spider assemblages. The observed shifts in the spider assemblages with increasing ant presence and plant species richness may have functional consequences, as web‐building and hunting spiders have distinct prey spectra. The relationships among ants, spiders, and plant species richness might contribute to explaining the non‐significant relationship between the overall effects of predators and plant diversity previously observed in the same forest plots. Our findings thus give insight into the complexity of biotic interactions in such species‐rich ecosystems.