Relative abundances of methane- and sulphur-oxidising symbionts in the gills of a cold seep mussel and link to their potential energy sources

Bathymodiolus mussels are key species in many deep-sea chemosynthetic ecosystems. They often harbour two types of endosymbiotic bacteria in their gills, sulphur- and methane oxidisers. These bacteria take up sulphide and methane from the environment and provide energy to their hosts, supporting some of the most prolific ecosystems in the sea. In this study, we tested whether symbiont relative abundances in Bathymodiolus gills reflect variations in the highly spatially dynamic chemical environment of cold seep mussels. Samples of Bathymodiolus aff. boomerang were obtained from two cold seeps of the deep Gulf of Guinea, REGAB (5°47.86S, 9°42.69E, 3170 m depth) and DIAPIR (6°41.58S, 10°20.94E, 2700 m depth). Relative abundances of both symbiont types were measured by means of 3D fluorescence in situ hybridisation and image analysis and compared considering the local sulphide and methane concentrations and fluxes assessed via benthic chamber incubations. Specimens inhabiting areas with highest methane content displayed higher relative abundances of methane oxidisers. The bacterial abundances correlated also with carbon stable isotope signatures in the mussel tissue, suggesting a higher contribution of methane-derived carbon to the biomass of mussels harbouring higher densities of methane-oxidising symbionts. A dynamic adaptation of abundances of methanotrophs and thiotrophs in the gill could be a key factor optimising the energy yield for the symbiotic system and could explain the success of dual symbiotic mussels at many cold seeps and hydrothermal vents of the Atlantic and Gulf of Mexico.     

How Deep-Sea Wood Falls Sustain Chemosynthetic Life

Large organic food falls to the deep sea – such as whale carcasses and wood logs – are known to serve as stepping stones for the dispersal of highly adapted chemosynthetic organisms inhabiting hot vents and cold seeps. Here we investigated the biogeochemical and microbiological processes leading to the development of sulfidic niches by deploying wood colonization experiments at a depth of 1690 m in the Eastern Mediterranean for one year. Wood-boring bivalves of the genus Xylophaga played a key role in the degradation of the wood logs, facilitating the development of anoxic zones and anaerobic microbial processes such as sulfate reduction. Fauna and bacteria associated with the wood included types reported from other deep-sea habitats including chemosynthetic ecosystems, confirming the potential role of large organic food falls as biodiversity hot spots and stepping stones for vent and seep communities. Specific bacterial communities developed on and around the wood falls within one year and were distinct from freshly submerged wood and background sediments. These included sulfate-reducing and cellulolytic bacterial taxa, which are likely to play an important role in the utilization of wood by chemosynthetic life and other deep-sea animals.     

RootScape: A Landmark-Based System for Rapid Screening of Root Architecture in Arabidopsis

The architecture of plant roots affects essential functions including nutrient and water uptake, soil anchorage, and symbiotic interactions. Root architecture comprises many features that arise from the growth of the primary and lateral roots. These root features are dictated by the genetic background but are also highly responsive to the environment. Thus, root system architecture (RSA) represents an important and complex trait that is highly variable, affected by genotype × environment interactions, and relevant to survival/performance. Quantification of RSA in Arabidopsis (Arabidopsis thaliana) using plate-based tissue culture is a very common and relatively rapid assay, but quantifying RSA represents an experimental bottleneck when it comes to medium- or high-throughput approaches used in mutant or genotype screens. Here, we present RootScape, a landmark-based allometric method for rapid phenotyping of RSA using Arabidopsis as a case study. Using the software AAMToolbox, we created a 20-point landmark model that captures RSA as one integrated trait and used this model to quantify changes in the RSA of Arabidopsis (Columbia) wild-type plants grown under different hormone treatments. Principal component analysis was used to compare RootScape with conventional methods designed to measure root architecture. This analysis showed that RootScape efficiently captured nearly all the variation in root architecture detected by measuring individual root traits and is 5 to 10 times faster than conventional scoring. We validated RootScape by quantifying the plasticity of RSA in several mutant lines affected in hormone signaling. The RootScape analysis recapitulated previous results that described complex phenotypes in the mutants and identified novel gene × environment interactions.Roots have a crucial impact on plant survival because of their major functions: anchorage of the plant in the soil, water and nutrient acquisition, and symbiotic interaction with other organisms (Den Herder et al., 2010). One important characteristic of root systems is the manner in which the primary and lateral roots comprise the superstructure or root architecture. Root architecture is an ideal system for studying developmental plasticity, as it continually integrates intrinsic and environmental responses (Malamy, 2005), which represents a vital and dynamic component of agricultural productivity (Lynch, 1995).Root system architecture (RSA) is defined as the spatial configuration of the roots in their environment (Lynch, 1995). The complexity of RSA was initially appreciated several decades ago, and terms like morphology, topology, distribution, and architecture were often used to describe the nature of RSA (Fitter, 1987; Fitter and Stickland, 1991; Lynch, 1995). These early reports argued that simple traits like root mass are insufficient to describe roots, because they do not capture the spatial configuration of roots in the soil, which is critical to plant performance (Fitter and Stickland, 1991). Root systems are integrated organs that adopt specific architectures to maximal foraging of the heterogeneous soil environment in different ways (Fitter, 1987; Fitter and Stickland, 1991; Lynch, 1995). More recently, new approaches have incorporated the measurement of many individual developmental traits that together comprise RSA (De Smet et al., 2012; Dubrovsky and Forde, 2012). For example, one recent report identified three fundamental components of RSA in generating complex topologies, including the contribution of lateral axes to branching, the rate and path of growth of the axis, and the increase in root surface area (Topp and Benfey, 2012). Thus, RSA is an important and complex trait that requires convenient measurement methods for rapid screening of diverse plant mutants and genotypes.With increasing research in RSA in the genetically tractable model plant Arabidopsis (Arabidopsis thaliana), the need for high-throughput methods of root phenotyping has dramatically increased over the years. Consequently, different methods and approaches have been developed in order to address this demand. Currently, three major approaches for phenotyping RSA are used (for review, see Zhu et al., 2011; De Smet et al., 2012). The first group of methods uses classical measures of RSA, which involve measurements of individual root traits. These methods often use software to manually draw the RSA onto digital two-dimensional images to quantify root length and number (Abramoff et al., 2004; http://www.machinevision.nl). These traditional methods provide the most accurate measurements of the root system but have a major disadvantage in being extremely time consuming.The second group of methods utilizes advanced semiautomated software for RSA measurements like EZ-Rhizo (Armengaud et al., 2009). EZ-Rhizo also uses digital two-dimensional images of plants grown on vertical plates (similar to the classical methods above) but is faster and produces different traits and basic statistics. The method works best when root features do not physically overlap, but we have found root overlap to be common when working with Arabidopsis plants older than 10 d. Other recent programs also provide semiautomated analysis of RSA, including RootReader2D (http://www.plantmineralnutrition.net/rootreader.htm) and SmartRoot (Lobet et al., 2011). However, while completely automated detection is potentially the highest throughput, we found that the root surface detection step is frequently prone to failure when using both of these programs, even after considerable adjustment by the user, where root features are missed or background noise is incorrectly labeled as roots.Finally, in a third group, recent developments include three-dimensional analysis of RSA of plants grown on transparent gel cylinders or in soil. The three-dimensional gel-based imaging approach is reported to be suitable for high-throughput phenotyping (Iyer-Pascuzzi et al., 2010). However, this approach requires special equipment, and imaging the root system of single plants can take 10 min (Iyer-Pascuzzi et al., 2010). X-ray computed tomography (Perret et al., 2007; Tracy et al., 2010) and magnetic resonance imaging (Van As, 2007) also provide highly detailed three-dimensional RSA analysis, but they require long scanning times and are extremely expensive and inaccessible. Most laboratories still utilize relatively convenient, inexpensive, and rapid two-dimensional phenotypic characterization of RSA, at least for initial screening purposes.The aim of this work is to address the need for a simple method to measure many different aspects of root architecture for high-throughput laboratory screening of mutants and genotypes in Arabidopsis. Here, we describe a landmark-based allometric (size and shape) approach called RootScape, a user-friendly software platform that enables rapid, comprehensive, and integrative phenotyping of the RSA in Arabidopsis. Unlike recent methods that collect information on different root traits to describe the RSA, RootScape places user-defined root landmarks on a two-dimensional grid to measure root architecture as a single integrated root system. The method employs rapid manual placement of root system landmarks. This manual step avoids one of the most problematic steps in automated image analysis (recognition of the root surface), providing a simple tool that does not require image processing. This method uses simple, two-dimensional digital images of the root system and a 20-point landmark model created in AAMToolbox, a freely available MATLAB plugin. While in-depth developmental analysis of root systems will often require knowing the contribution of individual traits, RootScape is a rapid method to access the holistic contribution of many individual root traits to RSA and to capture the overall property of the spatial configuration of roots in the soil (Fitter and Stickland, 1991). To demonstrate its utility, we used RootScape to quantify the root plasticity of Arabidopsis plants (Columbia [Col-0]) grown on four different media and compared the RootScape results with conventional measurements of individual root traits captured using the Optimas6 image-analysis software or Image J (Abramoff et al., 2004). This analysis showed that by measuring integrative root traits using RootScape, we could capture the vast majority of the individual trait variation, as verified by multiple regression analysis. Additionally, we tested the ability of RootScape to quantify the plasticity response in Arabidopsis mutants defective in hormone signaling. For this analysis, wild-type Col-0 and three hormone signaling mutants (auxin-resistant4 [axr4], abscisic acid insensitive4 [abi4], and cytokinin response1 [cre1]) were treated with auxin, cytokinin, or abscisic acid (ABA) versus controls. Statistical analyses (ANOVA/multivariate ANOVA [MANOVA]) allowed us to confirm most of the previously known interactions of genotype with these distinct environments and to potentially identify novel ones. Thus, we demonstrate that RootScape can be used as a rapid and efficient approach for quantifying the plasticity of the RSA in mutant (or ecotype) backgrounds of Arabidopsis and can identify new conditional root phenotypes.     

Spatial and temporal dynamics of hepatitis B virus D genotype in Europe and the Mediterranean Basin

Hepatitis B virus genotype D can be found in many parts of the world and is the most prevalent strain in south-eastern Europe, the Mediterranean Basin, the Middle East, and the Indian sub-continent. The epidemiological history of the D genotype and its subgenotypes is still obscure because of the scarcity of appropriate studies. We retrieved from public databases a total of 312 gene P sequences of HBV genotype D isolated in various countries throughout the world, and reconstructed the spatio-temporal evolutionary dynamics of the HBV-D epidemic using a bayesian framework.The phylogeographical analysis showed that India had the highest posterior probability of being the location of the tree root, whereas central Asia was the most probable location of the common ancestor of subgenotypes D1-D3. HBV-D5 (identified in native Indian populations) diverged from the tree root earlier than D1-D3. The time of the most recent common ancestor (tMRCA) of the tree root was 128 years ago, which suggests that the common ancestor of the currently circulating subgenotypes existed in the second half of the XIX century. The mean tMRCA of subgenotypes D1-D3 was between the 1940s and the 1950-60s. On the basis of our phylogeographic reconstruction, it seems that HBV-D reached the Mediterranean area in the middle of the XX century by means of at least two routes: the first pathway (mainly due to the spread of subgenotype D1) crossing the Middle East and reaching north Africa and the eastern Mediterranean, and the second pathway (closely associated with D2) that crossed the former Soviet Union and reached eastern Europe and the Mediterranean through Albania. We hypothesise that the main route of dispersion of genotype D was the unsafe use of injections and drug addiction.     

Feeding live prey to zoo animals: response of zoo visitors in Switzerland

In summer 2007, with the help of a written questionnaire, the attitudes of more than 400 visitors to the zoological garden of Zurich, Switzerland, toward the idea of feeding live insects to lizards, live fish to otters, and live rabbits to tigers were investigated. The majority of Swiss zoo visitors agreed with the idea of feeding live prey (invertebrates and vertebrates) to zoo animals, both off‐ and on‐exhibit, except in the case of feeding live rabbits to tigers on‐exhibit. Women and frequent visitors of the zoo disagreed more often with the on‐exhibit feeding of live rabbits to tigers. Study participants with a higher level of education were more likely to agree with the idea of feeding live invertebrates and vertebrates to zoo animals off‐exhibit. In comparison to an earlier study undertaken in Scotland, zoo visitors in Switzerland were more often in favor of the live feeding of vertebrates. Feeding live prey can counter the loss of hunting skills of carnivores and improve the animals' well‐being. However, feeding enrichments have to strike a balance between optimal living conditions of animals and the quality of visitor experience. Our results show that such a balance can be found, especially when live feeding of mammals is carried out off‐exhibit. A good interpretation of food enrichment might help zoos to win more support for the issue, and for re‐introduction programs and conservation. Zoo Biol 29:344–350, 2010. © 2009 Wiley‐Liss, Inc.     

Plasticity Regulators Modulate Specific Root Traits in Discrete Nitrogen Environments

Plant development is remarkably plastic but how precisely can the plant customize its form to specific environments? When the plant adjusts its development to different environments, related traits can change in a coordinated fashion, such that two traits co-vary across many genotypes. Alternatively, traits can vary independently, such that a change in one trait has little predictive value for the change in a second trait. To characterize such “tunability” in developmental plasticity, we carried out a detailed phenotypic characterization of complex root traits among 96 accessions of the model Arabidopsis thaliana in two nitrogen environments. The results revealed a surprising level of independence in the control of traits to environment – a highly tunable form of plasticity. We mapped genetic architecture of plasticity using genome-wide association studies and further used gene expression analysis to narrow down gene candidates in mapped regions. Mutants in genes implicated by association and expression analysis showed precise defects in the predicted traits in the predicted environment, corroborating the independent control of plasticity traits. The overall results suggest that there is a pool of genetic variability in plants that controls traits in specific environments, with opportunity to tune crop plants to a given environment.     

Focus Issue on Roots: Natural Variation of Root Traits: From Development to Nutrient Uptake

The root system has a crucial role for plant growth and productivity. Due to the challenges of heterogeneous soil environments, diverse environmental signals are integrated into root developmental decisions. While root growth and growth responses are genetically determined, there is substantial natural variation for these traits. Studying the genetic basis of the natural variation of root growth traits can not only shed light on their evolution and ecological relevance but also can be used to map the genes and their alleles responsible for the regulation of these traits. Analysis of root phenotypes has revealed growth strategies and root growth responses to a variety of environmental stimuli, as well as the extent of natural variation of a variety of root traits including ion content, cellular properties, and root system architectures. Linkage and association mapping approaches have uncovered causal genes underlying the variation of these traits.Since their advent more than 400 million years ago, vascular plants have drastically transformed the land surface of our planet and facilitated the dense colonization of its land masses (Algeo and Scheckler, 1998; Gibling and Davies, 2012). Key to this was the evolution of root systems that enable plants to forage their environment for nutrients and water and anchor themselves tightly in the soil substrate. Soils are very heterogeneous environments, and because of the constant need to optimize root distribution in the soil according to sometimes conflicting parameters, root growth and development are some of the most plastic traits in plants. This plasticity is guided by environmental information that is integrated into decisions regarding how fast and in which direction to grow and where and when to place new lateral roots (LRs; Malamy and Ryan, 2001; Malamy, 2005). The distribution and function of roots are of crucial importance for plants. In fact, they are considered the most limiting factors for plant growth in almost all natural ecosystems (Den Herder et al., 2010). Not surprisingly, the plant root system plays a major role in yield and overall plant productivity (Lynch, 1995; Den Herder et al., 2010).The extent of plasticity is determined by genetic components (Pigliucci, 2005). For instance, one ecotype of a plant species may be able to increase root growth rate on a certain stimulus, whereas another ecotype lacks this characteristic (Gifford et al., 2013). The genetic components that govern traits in different ecotypes represent the outcome of adaptation arising from the selection of those traits that allow better adapted populations to reproduce more successfully (higher fitness) than less well-adapted populations (Trontin et al., 2011; Savolainen, 2013). Although local adaptation is common in plants and animals, its genetic basis is still poorly understood (Savolainen et al., 2013). Traits that drive local adaptation are often quantitative traits shaped by multiple genes. Therefore, phenotypic differences are often caused by allelic variation at several loci, each of them making small contributions to the trait (Weigel and Nordborg, 2005; Rockman, 2012). Studying the genetic basis of the natural variation of traits cannot only shed light on the evolution of these traits and their ecological relevance but also, can be used to map the genes responsible for the regulation of these traits.Most efforts to study intraspecies genetic variation to find trait-governing genes or identify useful traits have been conducted in crop species and the model plant Arabidopsis (Arabidopsis thaliana). Whereas in crop species, traits that are used have been subjected to human-directed selection during domestication, often with the aim of increasing productivity, in Arabidopsis, it is mostly natural selection that is examined. Arabidopsis is widely distributed around the world, inhabiting diverse environments that include beaches, rocky slopes, riverbanks, roadsides, and areas surrounding agriculture fields (Horton et al., 2012). A large number of accessions has been collected over the past decades from locations all over the world and made available to the scientific community. Importantly, these accessions of Arabidopsis exhibit a striking diversity of phenotypic variation of morphology and physiology (Koornneef et al., 2004) and can be used to understand the genetic and molecular bases of traits using quantitative genetics. Variations of traits are measured in a panel of genetically distinct plant strains and then correlated with the occurrence of genetic markers in these plants. Linked or associated genome regions can eventually be identified, and additional analysis can be conducted to find the causal genes. Self-fertilizing species, such as Arabidopsis, are particularly suited for such approaches, because they can be maintained as inbred lines and therefore, need to be genotyped only one time, after which they can be phenotyped multiple times. In the past, natural variation has been used to map causal genes mainly by using recombinant inbred lines (RILs) approaches; these are very powerful but lack a high mapping resolution, and they can only capture a very small subset of the allelic diversity (Korte and Farlow, 2013). However, the advent of new and cheap large-scale genotyping and sequencing technologies has enabled large-scale, high-resolution genotyping (Horton et al., 2012) and even the complete sequencing of a large number of plant strains (http://1001genomes.org; 3,000 Rice Genomes Project, 2014). With these data, genome-wide association studies (GWASs) for identification of alleles responsible for many different quantitative traits have become feasible (Weigel, 2012). In these studies, traits of a large number of accessions are measured and subsequently associated with genotyped markers, most frequently single-nucleotide polymorphism. Although GWASs are a very powerful tool and in principle, allow for a high mapping accuracy, a notable disadvantage is that the complexity of the population structure can confound these studies. However, there has been remarkable progress addressing this issue (Atwell et al., 2010; Segura et al., 2012).In this review, we highlight recent progress in understanding the genetic bases of natural variation of growth, development, and physiology of the root system. After briefly explaining how root growth and development give rise to the root system architecture (RSA), we highlight natural variation and what has been learned from it for fundamental processes in root growth and development, root growth responses to nutrient availability, and ion uptake and homeostasis.     

Bacterial Diversity in the South Adriatic Sea during a Strong,Deep Winter Convection Year

The South Adriatic Sea is the deepest part of the Adriatic Sea and represents a key area for both the Adriatic Sea and the deep eastern Mediterranean. It has a role in dense water formation for the eastern Mediterranean deep circulation cell, and it represents an entry point for water masses originating from the Ionian Sea. The biodiversity and seasonality of bacterial picoplankton before, during, and after deep winter convection in the oligotrophic South Adriatic waters were assessed by combining comparative 16S rRNA sequence analysis and catalyzed reporter deposition-fluorescence in situ hybridization (CARD-FISH). The picoplankton communities reached their maximum abundance in the spring euphotic zone when the maximum value of the chlorophyll a in response to deep winter convection was recorded. The communities were dominated by Bacteria, while Archaea were a minor constituent. A seasonality of bacterial richness and diversity was observed, with minimum values occurring during the winter convection and spring postconvection periods and maximum values occurring under summer stratified conditions. The SAR11 clade was the main constituent of the bacterial communities and reached the maximum abundance in the euphotic zone in spring after the convection episode. Cyanobacteria were the second most abundant group, and their abundance strongly depended on the convection event, when minimal cyanobacterial abundance was observed. In spring and autumn, the euphotic zone was characterized by Bacteroidetes and Gammaproteobacteria. Bacteroidetes clades NS2b, NS4, and NS5 and the gammaproteobacterial SAR86 clade were detected to co-occur with phytoplankton blooms. The SAR324, SAR202, and SAR406 clades were present in the deep layer, exhibiting different seasonal variations in abundance. Overall, our data demonstrate that the abundances of particular bacterial clades and the overall bacterial richness and diversity are greatly impacted by strong winter convection.     

Spatial scales of bacterial community diversity at cold seeps (Eastern Mediterranean Sea)

Cold seeps are highly productive, fragmented marine ecosystems that form at the seafloor around hydrocarbon emission pathways. The products of microbial utilization of methane and other hydrocarbons fuel rich chemosynthetic communities at these sites, with much higher respiration rates compared with the surrounding deep-sea floor. Yet little is known as to the richness, composition and spatial scaling of bacterial communities of cold seeps compared with non-seep communities. Here we assessed the bacterial diversity across nine different cold seeps in the Eastern Mediterranean deep-sea and surrounding seafloor areas. Community similarity analyses were carried out based on automated ribosomal intergenic spacer analysis (ARISA) fingerprinting and high-throughput 454 tag sequencing and were combined with in situ and ex situ geochemical analyses across spatial scales of a few tens of meters to hundreds of kilometers. Seep communities were dominated by Deltaproteobacteria, Epsilonproteobacteria and Gammaproteobacteria and shared, on average, 36% of bacterial types (ARISA OTUs (operational taxonomic units)) with communities from nearby non-seep deep-sea sediments. Bacterial communities of seeps were significantly different from those of non-seep sediments. Within cold seep regions on spatial scales of only tens to hundreds of meters, the bacterial communities differed considerably, sharing <50% of types at the ARISA OTU level. Their variations reflected differences in porewater sulfide concentrations from anaerobic degradation of hydrocarbons. This study shows that cold seep ecosystems contribute substantially to the microbial diversity of the deep-sea.