Linking Hydrothermal Geochemistry to Organismal Physiology: Physiological Versatility in Riftia pachyptila from Sedimented and Basalt-hosted Vents

Much of what is known regarding Riftia pachyptila physiology is based on the wealth of studies of tubeworms living at diffuse flows along the fast-spreading, basalt-hosted East Pacific Rise (EPR). These studies have collectively suggested that Riftia pachyptila and its chemoautotrophic symbionts are physiologically specialized, highly productive associations relying on hydrogen sulfide and oxygen to generate energy for carbon fixation, and the symbiont's nitrate reduction to ammonia for energy and biosynthesis. However, Riftia also flourish in sediment-hosted vents, which are markedly different in geochemistry than basalt-hosted systems. Here we present data from shipboard physiological studies and global quantitative proteomic analyses of Riftia pachyptila trophosome tissue recovered from tubeworms residing in the EPR and the Guaymas basin, a sedimented, hydrothermal vent field. We observed marked differences in symbiont nitrogen metabolism in both the respirometric and proteomic data. The proteomic data further suggest that Riftia associations in Guaymas may utilize different sulfur compounds for energy generation, may have an increased capacity for energy storage, and may play a role in degrading exogenous organic carbon. Together these data reveal that Riftia symbionts are far more physiologically plastic than previously considered, and that -contrary to previous assertions- Riftia do assimilate reduced nitrogen in some habitats. These observations raise new hypotheses regarding adaptations to the geochemical diversity of habitats occupied by Riftia, and the degree to which the environment influences symbiont physiology and evolution

Nitrate respiration in the hydrothermal vent tubeworm Riftia pachyptila

THE vestimentiferan tubeworm Riftia pachyptila is found around hydrothermal vent areas in the deep sea. Intracellular bacterial chemoautotrophic symbionts use the oxidation of sulphide from the effluent of the vents as an energy source for CO2 fixation. They apparently provide most or all of the nutritional requirements for their gutless hosts1–5. This kind of symbiosis has since been found in many other species from various other phyla from other habitats6–9. Here we present results that the bacteria of R. pachyptila may cover a significant fraction of their respiratory needs by the use of nitrate in addition to oxygen. Nitrate is reduced to nitrite, which may be the end product (nitrate respiration)10 or it may be further reduced to nitrogen gas (denitrification)11. This metabolic trait may have an important role in the colonization of hypoxic habitats in general by animals with this kind of symbiosis

On the evolutionary ecology of symbioses between chemosynthetic bacteria and bivalves

Mutualistic associations between bacteria and eukaryotes occur ubiquitously in nature, forming the basis for key ecological and evolutionary innovations. Some of the most prominent examples of these symbioses are chemosynthetic bacteria and marine invertebrates living in the absence of sunlight at deep-sea hydrothermal vents and in sediments rich in reduced sulfur compounds. Here, chemosynthetic bacteria living in close association with their hosts convert CO2 or CH4 into organic compounds and provide the host with necessary nutrients. The dominant macrofauna of hydrothermal vent and cold seep ecosystems all depend on the metabolic activity of chemosynthetic bacteria, which accounts for almost all primary production in these complex ecosystems. Many of these enigmatic mutualistic associations are found within the molluscan class Bivalvia. Currently, chemosynthetic symbioses have been reported from five distinct bivalve families (Lucinidae, Mytilidae, Solemyidae, Thyasiridae, and Vesicomyidae). This brief review aims to provide an overview of the diverse physiological and genetic adaptations of symbiotic chemosynthetic bacteria and their bivalve hosts

Search for sterile neutrino mixing in the MINOS long-baseline experiment

A search for depletion of the combined flux of active neutrino species over a 735 km baseline is reported using neutral-current interaction data recorded by the MINOS detectors in the NuMI neutrino beam. Such a depletion is not expected according to conventional interpretations of neutrino oscillation data involving the three known neutrino flavors. A depletion would be a signature of oscillations or decay to postulated noninteracting sterile neutrinos, scenarios not ruled out by existing data. From an exposure of 3.18×1020 protons on target in which neutrinos of energies between ~500¿¿MeV and 120 GeV are produced predominantly as ¿µ, the visible energy spectrum of candidate neutral-current reactions in the MINOS far detector is reconstructed. Comparison of this spectrum to that inferred from a similarly selected near-detector sample shows that of the portion of the ¿µ flux observed to disappear in charged-current interaction data, the fraction that could be converting to a sterile state is less than 52% at 90% confidence level (C.L.). The hypothesis that active neutrinos mix with a single sterile neutrino via oscillations is tested by fitting the data to various models. In the particular four-neutrino models considered, the mixing angles ¿24 and ¿34 are constrained to be less than 11° and 56° at 90% C.L., respectively. The possibility that active neutrinos may decay to sterile neutrinos is also investigated. Pure neutrino decay without oscillations is ruled out at 5.4 standard deviations. For the scenario in which active neutrinos decay into sterile states concurrently with neutrino oscillations, a lower limit is established for the neutrino decay lifetime t3/m3>2.1×10-12¿¿s/eV at 90% C.L

Neuronal circuitry for pain processing in the dorsal horn

Neurons in the spinal dorsal horn process sensory information, which is then transmitted to several brain regions, including those responsible for pain perception. The dorsal horn provides numerous potential targets for the development of novel analgesics and is thought to undergo changes that contribute to the exaggerated pain felt after nerve injury and inflammation. Despite its obvious importance, we still know little about the neuronal circuits that process sensory information, mainly because of the heterogeneity of the various neuronal components that make up these circuits. Recent studies have begun to shed light on the neuronal organization and circuitry of this complex region

Plague and Climate: Scales Matter

Plague is enzootic in wildlife populations of small mammals in central and eastern Asia, Africa, South and North America, and has been recognized recently as a reemerging threat to humans. Its causative agent Yersinia pestis relies on wild rodent hosts and flea vectors for its maintenance in nature. Climate influences all three components (i.e., bacteria, vectors, and hosts) of the plague system and is a likely factor to explain some of plague's variability from small and regional to large scales. Here, we review effects of climate variables on plague hosts and vectors from individual or population scales to studies on the whole plague system at a large scale. Upscaled versions of small-scale processes are often invoked to explain plague variability in time and space at larger scales, presumably because similar scale-independent mechanisms underlie these relationships. This linearity assumption is discussed in the light of recent research that suggests some of its limitations

Dancing for Food in the Deep Sea: Bacterial Farming by a New Species of Yeti Crab

Vent and seep animals harness chemosynthetic energy to thrive far from the sun's energy. While symbiont-derived energy fuels many taxa, vent crustaceans have remained an enigma; these shrimps, crabs, and barnacles possess a phylogenetically distinct group of chemosynthetic bacterial epibionts, yet the role of these bacteria has remained unclear. We test whether a new species of Yeti crab, which we describe as Kiwa puravida n. sp, farms the epibiotic bacteria that it grows on its chelipeds (claws), chelipeds that the crab waves in fluid escaping from a deep-sea methane seep. Lipid and isotope analyses provide evidence that epibiotic bacteria are the crab's main food source and K. puravida n. sp. has highly-modified setae (hairs) on its 3rd maxilliped (a mouth appendage) which it uses to harvest these bacteria. The ε- and γ- proteobacteria that this methane-seep species farms are closely related to hydrothermal-vent decapod epibionts. We hypothesize that this species waves its arm in reducing fluid to increase the productivity of its epibionts by removing boundary layers which may otherwise limit carbon fixation. The discovery of this new species, only the second within a family described in 2005, stresses how much remains undiscovered on our continental margins

An Empirical Comparison of Information-Theoretic Criteria in Estimating the Number of Independent Components of fMRI Data

BACKGROUND: Independent Component Analysis (ICA) has been widely applied to the analysis of fMRI data. Accurate estimation of the number of independent components of fMRI data is critical to reduce over/under fitting. Although various methods based on Information Theoretic Criteria (ITC) have been used to estimate the intrinsic dimension of fMRI data, the relative performance of different ITC in the context of the ICA model hasn't been fully investigated, especially considering the properties of fMRI data. The present study explores and evaluates the performance of various ITC for the fMRI data with varied white noise levels, colored noise levels, temporal data sizes and spatial smoothness degrees. METHODOLOGY: Both simulated data and real fMRI data with varied Gaussian white noise levels, first-order auto-regressive (AR(1)) noise levels, temporal data sizes and spatial smoothness degrees were carried out to deeply explore and evaluate the performance of different traditional ITC. PRINCIPAL FINDINGS: Results indicate that the performance of ITCs depends on the noise level, temporal data size and spatial smoothness of fMRI data. 1) High white noise levels may lead to underestimation of all criteria and MDL/BIC has the severest underestimation at the higher Gaussian white noise level. 2) Colored noise may result in overestimation that can be intensified by the increase of AR(1) coefficient rather than the SD of AR(1) noise and MDL/BIC shows the least overestimation. 3) Larger temporal data size will be better for estimation for the model of white noise but tends to cause severer overestimation for the model of AR(1) noise. 4) Spatial smoothing will result in overestimation in both noise models. CONCLUSIONS: 1) None of ITC is perfect for all fMRI data due to its complicated noise structure. 2) If there is only white noise in data, AIC is preferred when the noise level is high and otherwise, Laplace approximation is a better choice. 3) When colored noise exists in data, MDL/BIC outperforms the other criteria