Basin-scale transport of hydrothermal dissolved metals across the South Pacific Ocean

Hydrothermal venting along mid-ocean ridges exerts an important control on the chemical composition of sea water by serving as a major source or sink for a number of trace elements in the ocean(1-3). Of these, iron has received considerable attention because of its role as an essential and often limiting nutrient for primary production in regions of the ocean that are of critical importance for the global carbon cycle(4). It has been thought that most of the dissolved iron discharged by hydrothermal vents is lost from solution close to ridge-axis sources(2,5) and is thus of limited importance for ocean biogeochemistry(6). This long-standing view is challenged by recent studies which suggest that stabilization of hydrothermal dissolved iron may facilitate its longrange oceanic transport(7-10). Such transport has been subsequently inferred from spatially limited oceanographic observations(11-13). Here we report data from the US GEOTRACES Eastern Pacific Zonal Transect (EPZT) that demonstrate lateral transport of hydrothermal dissolved iron, manganese, and aluminium from the southern East Pacific Rise (SEPR) several thousand kilometres westward across the South Pacific Ocean. Dissolved iron exhibits nearly conservative (that is, no loss from solution during transport and mixing) behaviour in this hydrothermal plume, implying a greater longevity in the deep ocean than previously assumed(6,14). Based on our observations, we estimate a global hydrothermal dissolved iron input of three to four gigamoles per year to the ocean interior, which is more than fourfold higher than previous estimates(7,11,14). Complementary simulations with a global-scale ocean biogeochemical model suggest that the observed transport of hydrothermal dissolved iron requires some means of physicochemical stabilization and indicate that hydrothermally derived iron sustains a large fraction of Southern Ocean export productio

The submarine volcano eruption at the island of El Hierro: physical-chemical perturbation and biological response

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Harvest: an open-source tool for the validation and improvement of peptide identification metrics and fragmentation exploration

<p>Abstract</p> <p>Background</p> <p>Protein identification using mass spectrometry is an important tool in many areas of the life sciences, and in proteomics research in particular. Increasing the number of proteins correctly identified is dependent on the ability to include new knowledge about the mass spectrometry fragmentation process, into computational algorithms designed to separate true matches of peptides to unidentified mass spectra from spurious matches. This discrimination is achieved by computing a function of the various features of the potential match between the observed and theoretical spectra to give a numerical approximation of their similarity. It is these underlying "metrics" that determine the ability of a protein identification package to maximise correct identifications while limiting false discovery rates. There is currently no software available specifically for the simple implementation and analysis of arbitrary novel metrics for peptide matching and for the exploration of fragmentation patterns for a given dataset.</p> <p>Results</p> <p>We present Harvest: an open source software tool for analysing fragmentation patterns and assessing the power of a new piece of information about the MS/MS fragmentation process to more clearly differentiate between correct and random peptide assignments. We demonstrate this functionality using data metrics derived from the properties of individual datasets in a peptide identification context. Using Harvest, we demonstrate how the development of such metrics may improve correct peptide assignment confidence in the context of a high-throughput proteomics experiment and characterise properties of peptide fragmentation.</p> <p>Conclusions</p> <p>Harvest provides a simple framework in C++ for analysing and prototyping metrics for peptide matching, the core of the protein identification problem. It is not a protein identification package and answers a different research question to packages such as Sequest, Mascot, X!Tandem, and other protein identification packages. It does not aim to maximise the number of assigned peptides from a set of unknown spectra, but instead provides a method by which researchers can explore fragmentation properties and assess the power of novel metrics for peptide matching in the context of a given experiment. Metrics developed using Harvest may then become candidates for later integration into protein identification packages.</p

Hydrothermal Stamp on the Oceans

The composition of the oceans is altered by hydrothermal circulation. These chemical factories sustain microbial life, which in turn alters the chemistry of the fuids that enter the ocean. A decade of research details this complex interchange

Comment on "Evidence from acoustic imaging for submarine volcanic activity in 2012 off the west coast of El Hierro (Canary Islands, Spain)" by Pérez NM, Somoza L, Hernández PA, González de Vallejo L, León R, Sagiya T, Biain A, González FJ, Medialdea T, Barrancos J, Ibáñez J, Sumino H, Nogami K and Romero C [Bull Volcanol (2014) 76:882-896]

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Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology

Iron Biogeochemistry in the High Latitude North Atlantic Ocean

Iron (Fe) is an essential micronutrient for marine microbial organisms, and low supply controls productivity in large parts of the world’s ocean. The high latitude North Atlantic is seasonally Fe limited, but Fe distributions and source strengths are poorly constrained. Surface ocean dissolved Fe (DFe) concentrations were low in the study region (<0.1 nM) in summer 2010, with significant perturbations during spring 2010 in the Iceland Basin as a result of an eruption of the Eyjafjallajökull volcano (up to 2.5 nM DFe near Iceland) with biogeochemical consequences. Deep water concentrations in the vicinity of the Reykjanes Ridge system were influenced by pronounced sediment resuspension, with indications for additional inputs by hydrothermal vents, with subsequent lateral transport of Fe and manganese plumes of up to 250–300 km. Particulate Fe formed the dominant pool, as evidenced by 4–17 fold higher total dissolvable Fe compared with DFe concentrations, and a dynamic exchange between the fractions appeared to buffer deep water DFe. Here we show that Fe supply associated with deep winter mixing (up to 103 nmol m−2 d−1) was at least ca. 4–10 times higher than atmospheric deposition, diffusive fluxes at the base of the summer mixed layer, and horizontal surface ocean fluxes

Biotic and abiotic retention, recycling and remineralization of metals in the ocean

Trace metals shape both the biogeochemical functioning and biological structure of oceanic provinces. Trace metal biogeochemistry has primarily focused on modes of external supply of metals from aeolian, hydrothermal, sedimentary and other sources. However, metals also undergo internal transformations such as abiotic and biotic retention, recycling and remineralization. The role of these internal transformations in metal biogeochemical cycling is now coming into focus. First, the retention of metals by biota in the surface ocean for days, weeks or months depends on taxon-specific metal requirements of phytoplankton, and on their ultimate fate: that is, viral lysis, senescence, grazing and/or export to depth. Rapid recycling of metals in the surface ocean can extend seasonal productivity by maintaining higher levels of metal bioavailability compared to the influence of external metal input alone. As metal-containing organic particles are exported from the surface ocean, different metals exhibit distinct patterns of remineralization with depth. These patterns are mediated by a wide range of physicochemical and microbial processes such as the ability of particles to sorb metals, and are influenced by the mineral and organic characteristics of sinking particles. We conclude that internal metal transformations play an essential role in controlling metal bioavailability, phytoplankton distributions and the subsurface resupply of metals

Chimerism in Wild Adult Populations of the Broadcast Spawning Coral Acropora millepora on the Great Barrier Reef

Chimeras are organisms containing tissues or cells of two or more genetically distinct individuals, and are known to exist in at least nine phyla of protists, plants, and animals. Although widespread and common in marine invertebrates, the extent of chimerism in wild populations of reef corals is unknown.The extent of chimerism was explored within two populations of a common coral, Acropora millepora, on the Great Barrier Reef, Australia, by using up to 12 polymorphic DNA microsatellite loci. At least 2% and 5% of Magnetic Island and Pelorus Island populations of A. millepora, respectively, were found to be chimeras (3% overall), based on conservative estimates. A slightly less conservative estimate indicated that 5% of colonies in each population were chimeras. These values are likely to be vast underestimates of the true extent of chimerism, as our sampling protocol was restricted to a maximum of eight branches per colony, while most colonies consist of hundreds of branches. Genotypes within chimeric corals showed high relatedness, indicating that genetic similarity is a prerequisite for long-term acceptance of non-self genotypes within coral colonies.While some brooding corals have been shown to form genetic chimeras in their early life history stages under experimental conditions, this study provides the first genetic evidence of the occurrence of coral chimeras in the wild and of chimerism in a broadcast spawning species. We hypothesize that chimerism is more widespread in corals than previously thought, and suggest that this has important implications for their resilience, potentially enhancing their capacity to compete for space and respond to stressors such as pathogen infection

A proteomics approach to decipher the molecular nature of planarian stem cells

Background In recent years, planaria have emerged as an important model system for research into stem cells and regeneration. Attention is focused on their unique stem cells, the neoblasts, which can differentiate into any cell type present in the adult organism. Sequencing of the Schmidtea mediterranea genome and some expressed sequence tag projects have generated extensive data on the genetic profile of these cells. However, little information is available on their protein dynamics. Results We developed a proteomic strategy to identify neoblast-specific proteins. Here we describe the method and discuss the results in comparison to the genomic high-throughput analyses carried out in planaria and to proteomic studies using other stem cell systems. We also show functional data for some of the candidate genes selected in our proteomic approach. Conclusions We have developed an accurate and reliable mass-spectra-based proteomics approach to complement previous genomic studies and to further achieve a more accurate understanding and description of the molecular and cellular processes related to the neoblasts