Fungal communities living within leaves of native Hawaiian dicots are structured by landscape‐scale variables as well as by host plants

A phylogenetically diverse array of fungi live within healthy leaf tissue of dicotyledonous plants. Many studies have examined these endophytes within a single plant species and/or at small spatial scales, but landscape‐scale variables that determine their community composition are not well understood, either across geographic space, across climatic conditions, or in the context of host plant phylogeny. Here, we evaluate the contributions of these variables to endophyte beta diversity using a survey of foliar endophytic fungi in native Hawaiian dicots sampled across the Hawaiian archipelago. We used Illumina technology to sequence fungal ITS1 amplicons to characterize foliar endophyte communities across five islands and 80 host plant genera. We found that communities of foliar endophytic fungi showed strong geographic structuring between distances of 7 and 36 km. Endophyte community structure was most strongly associated with host plant phylogeny and evapotranspiration, and was also significantly associated with NDVI, elevation and solar radiation. Additionally, our bipartite network analysis revealed that the five islands we sampled each harboured significantly specialized endophyte communities. These results demonstrate how the interaction of factors at large and small spatial and phylogenetic scales shapes fungal symbiont communities.     

One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE

Improved efficiency of Markov chain Monte Carlo facilitates all aspects of statistical analysis with Bayesian hierarchical models. Identifying strategies to improve MCMC performance is becoming increasingly crucial as the complexity of models, and the run times to fit them, increases. We evaluate different strategies for improving MCMC efficiency using the open‐source software NIMBLE (R package nimble) using common ecological models of species occurrence and abundance as examples. We ask how MCMC efficiency depends on model formulation, model size, data, and sampling strategy. For multiseason and/or multispecies occupancy models and for N‐mixture models, we compare the efficiency of sampling discrete latent states vs. integrating over them, including more vs. fewer hierarchical model components, and univariate vs. block‐sampling methods. We include the common MCMC tool JAGS in comparisons. For simple models, there is little practical difference between computational approaches. As model complexity increases, there are strong interactions between model formulation and sampling strategy on MCMC efficiency. There is no one‐size‐fits‐all best strategy, but rather problem‐specific best strategies related to model structure and type. In all but the simplest cases, NIMBLE's default or customized performance achieves much higher efficiency than JAGS. In the two most complex examples, NIMBLE was 10–12 times more efficient than JAGS. We find NIMBLE is a valuable tool for many ecologists utilizing Bayesian inference, particularly for complex models where JAGS is prohibitively slow. Our results highlight the need for more guidelines and customizable approaches to fit hierarchical models to ensure practitioners can make the most of occupancy and other hierarchical models. By implementing model‐generic MCMC procedures in open‐source software, including the NIMBLE extensions for integrating over latent states (implemented in the R package nimbleEcology), we have made progress toward this aim.     

The role of alanine synthesis and nitrate-induced nitric oxide production during hypoxia stress in Cucurbita pepo nectaries

Floral nectar is a sugary solution produced by nectaries to attract and reward pollinators. Nectar metabolites, such as sugars, are synthesized within the nectary during secretion from both pre-stored and direct phloem-derived precursors. In addition to sugars, nectars contain nitrogenous compounds such as amino acids; however, little is known about the role(s) of nitrogen (N) compounds in nectary function. In this study, we investigated N metabolism in Cucurbita pepo (squash) floral nectaries in order to understand how various N-containing compounds are produced and determine the role of N metabolism in nectar secretion. The expression and activity of key enzymes involved in primary N assimilation, including nitrate reductase (NR) and alanine aminotransferase (AlaAT), were induced during secretion in C. pepo nectaries. Alanine (Ala) accumulated to about 35% of total amino acids in nectaries and nectar during peak secretion; however, alteration of vascular nitrate supply had no impact on Ala accumulation during secretion, suggesting that nectar(y) amino acids are produced by precursors other than nitrate. In addition, nitric oxide (NO) is produced from nitrate and nitrite, at least partially by NR, in nectaries and nectar. Hypoxia-related processes are induced in nectaries during secretion, including lactic acid and ethanolic fermentation. Finally, treatments that alter nitrate supply affect levels of hypoxic metabolites, nectar volume and nectar sugar composition. The induction of N metabolism in C. pepo nectaries thus plays an important role in the synthesis and secretion of nectar sugar.     

Application of plant metabarcoding to identify diverse honeybee pollen forage along an urban–agricultural gradient

Understanding animal foraging ecology requires large sample sizes spanning broad environmental and temporal gradients. For pollinators, this has been hampered by the laborious nature of morphologically identifying pollen. Identifying pollen from urban environments is particularly difficult due to the presence of diverse ornamental species associated with consumer horticulture. Metagenetic pollen analysis represents a potential solution to this issue. Building upon prior laboratory and bioinformatic methods, we applied quantitative multilocus metabarcoding to characterize the foraging ecology of honeybee colonies situated in urban, suburban, mixed suburban–agricultural and rural agricultural sites in central Ohio, USA. In cross‐validating a subset of our metabarcoding results using microscopic palynology, we find strong concordance between the molecular and microscopic methods. Our results suggest that forage from the agricultural site exhibited decreased taxonomic diversity and temporal turnover relative to the urban and suburban sites, though the generalization of this observation will require replication across additional sites and cities. Our work demonstrates the power of honeybees as environmental samplers of floral community composition at large spatial scales, aiding in the distinction of taxa characteristically associated with urban or agricultural land use from those distributed ubiquitously across the sampled landscapes. Observed patterns of high forage diversity and compositional turnover in our more urban sites are likely reflective of the fine‐grain heterogeneity and high beta diversity of urban floral landscapes at the scale of honeybee foraging. This provides guidance for future studies investigating how relationships between urbanization and measures of pollinator health are mediated by variation in floral resource dynamics across landscapes.     

Large vertical movements by a goosefish,Lophius americanus,suggests the potential of data storage tags for behavioral studies of benthic fishes

The extensive periodic vertical movements of up to 14 h and 209 m observed in this study for an individual goosefish, Lophius americanus, challenges previous assumptions about the benthic and highly sedentary behavior of the species as well as of other lophiids. Researchers should consider conducting similar data storage tagging studies with other benthic fishes to test assumptions of sedentary behavior.     

Influence of inlet boundary conditions on the local haemodynamics of intracranial aneurysms

Haemodynamics is believed to play an important role in the initiation, growth and rupture of intracranial aneurysms. In this context, computational haemodynamics has been extensively used in an effort to establish correlations between flow variables and clinical outcome. It is common practice in the application of Dirichlet boundary conditions at domain inlets to specify transient velocities as either a flat (plug) profile or a spatially developed profile based on Womersley's analytical solution. This paper provides comparative haemodynamics measures for three typical cerebral aneurysms.

Three dimentional rotational angiography images of aneurysms at three common locations, viz. basilar artery tip, internal carotid artery and middle cerebral artery were obtained. The computational tools being developed in the European project @neurIST were used to reconstruct the fluid domains and solve the unsteady Navier–Stokes equations, using in turn Womersley and plug-flow inlet velocity profiles. The effects of these assumptions were analysed and compared in terms of relevant haemodynamic variables within the aneurismal sac. For the aneurysm at the basilar tip geometries with different extensions of the afferent vasculature were considered to study the plausibility of a fully-developed axial flow at the inlet boundaries.

The study shows that assumptions made on the velocity profile while specifying inlet boundary conditions have little influence on the local haemodynamics in the aneurysm, provided that a sufficient extension of the afferent vasculature is considered and that geometry is the primary determinant of the flow field within the aneurismal sac. For real geometries the Womersley profile is at best an unnecessary over-complication, and may even be worse than the plug profile in some anatomical locations (e.g. basilar confluence).     

The Radical SAM Superfamily

ABSTRACT

The radical S-adenosylmethionine (SAM) superfamily currently comprises more than 2800 proteins with the amino acid sequence motif CxxxCxxC unaccompanied by a fourth conserved cysteine. The charcteristic three-cysteine motif nucleates a [4Fe–4S] cluster, which binds SAM as a ligand to the unique Fe not ligated to a cysteine residue. The members participate in more than 40 distinct biochemical transformations, and most members have not been biochemically characterized. A handful of the members of this superfamily have been purified and at least partially characterized. Significant mechanistic and structural information is available for lysine 2,3-aminomutase, pyruvate formate-lyase, coproporphyrinogen III oxidase, and MoaA required for molybdopterin biosynthesis. Biochemical information is available for spore photoproduct lyase, anaerobic ribonucleotide reductase activation subunit, lipoyl synthase, and MiaB involved in methylthiolation of isopentenyladenine-37 in tRNA. The radical SAM enzymes biochemically characterized to date have in common the cleavage of the [4Fe–4S]^{1 +} –SAM complex to [4Fe–4S]^{2 +}–Met and the 5′ -deoxyadenosyl radical, which abstracts a hydrogen atom from the substrate to initiate a radical mechanism.     

Estimating the Toxicity of Pesticide Mixtures to Aquatic Organisms: A Review

A major difficulty in addressing chemical mixtures through legislation or regulations revolves around our limited understanding of their potential impacts. This review provides an overview of recent research on pesticide mixture toxicity to aquatic biota and the methods employed to predict toxic effects. The most common approaches are to assume concentration-addition or independent action of chemicals in a mixture. There are a number of cases in the literature of interactions between pesticides. However, models accounting for possible interactions between mixture components are used infrequently. Although results are limited, studies investigating the effects of pesticide mixtures have not demonstrated significant synergism at environmentally relevant concentrations. Based on the results of our review, we conclude that the concentration-addition model is a generally conservative and practical first-tier model for the ecological assessment of pesticide mixtures in aquatic systems.     

Purification of Monoclonal Antibodies Using High Performance Liquid Chromatography (HPLC)

Recent increases in the ability to detect low levels of immunofluorescence have shown the need for highly purified primary immunoreagents. There are now reports of purification of monoclonal antibodies using HPLC with reverse phase columns. In this study we have utilized standard size exclusion HPLC to purify both biotinylated and non-biotinylated monoclonal antibodies from hybridoma culture supernatants. Results indicated that both biotinylated and non-biotinylated monoclonal antibodies retained their antigen binding capacity after purification, and were not different in this capacity from commercially available, affinity purified reagents. These findings indicate that size exclusion HPLC may be used in the purification of biologically active monoclonal antibodies, and suggest that this technique may be used in the large scale production of antibodies and their fragments, in antibody purification from ascites fluid, and in antisera quality control.