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1. A Fourfold Pathogen Reference Ontology Suite

Author

Babcock, Shane, Benson, Carter, De Colle, Giacomo, Cohen, Sydney, Diehl, Alexander D., Challa, Ram A. N. R., Huffman, Anthony, He, Yongqun, and Beverley, John

Subjects
Quantitative Biology - Other Quantitative Biology, Computer Science - Artificial Intelligence, Computer Science - Logic in Computer Science
Abstract

Infectious diseases remain a critical global health challenge, and the integration of standardized ontologies plays a vital role in managing related data. The Infectious Disease Ontology (IDO) and its extensions, such as the Coronavirus Infectious Disease Ontology (CIDO), are essential for organizing and disseminating information related to infectious diseases. The COVID-19 pandemic highlighted the need for updating IDO and its virus-specific extensions. There is an additional need to update IDO extensions specific to bacteria, fungus, and parasite infectious diseases. We adopt the "hub and spoke" methodology to generate pathogen-specific extensions of IDO: Virus Infectious Disease Ontology (VIDO), Bacteria Infectious Disease Ontology (BIDO), Mycosis Infectious Disease Ontology (MIDO), and Parasite Infectious Disease Ontology (PIDO). The creation of pathogen-specific reference ontologies advances modularization and reusability of infectious disease data within the IDO ecosystem. Future work will focus on further refining these ontologies, creating new extensions, and developing application ontologies based on them, in line with ongoing efforts to standardize biological and biomedical terminologies for improved data sharing and analysis., Comment: 25 pages

Published
2024

2. Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)

Author

Toro, Sabrina, Anagnostopoulos, Anna V, Bello, Susan M, Blumberg, Kai, Cameron, Rhiannon, Carmody, Leigh, Diehl, Alexander D, Dooley, Damion M, Duncan, William D, Fey, Petra, Gaudet, Pascale, Harris, Nomi L, Joachimiak, Marcin P, Kiani, Leila, Lubiana, Tiago, Munoz-Torres, Monica C, O‘Neil, Shawn, Osumi-Sutherland, David, Puig-Barbe, Aleix, Reese, Justin T, Reiser, Leonore, Robb, Sofia MC, Ruemping, Troy, Seager, James, Sid, Eric, Stefancsik, Ray, Weber, Magalie, Wood, Valerie, Haendel, Melissa A, and Mungall, Christopher J

Subjects
Data Management and Data Science, Information and Computing Sciences, Artificial Intelligence, Networking and Information Technology R&D (NITRD), Generic health relevance, Biological Ontologies, Natural Language Processing, Information Storage and Retrieval, Artificial intelligence, Biocuration, Knowledge graphs, Large language models, Ontologies, Ontology engineering, Other Biological Sciences, Artificial Intelligence and Image Processing, Information Systems, Information and computing sciences
Abstract

BackgroundOntologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources.ResultsWe assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues.ConclusionsThese findings suggest DRAGON-AI's potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

Published
2024

3. Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)

Author

Toro, Sabrina, Anagnostopoulos, Anna V, Bello, Sue, Blumberg, Kai, Cameron, Rhiannon, Carmody, Leigh, Diehl, Alexander D, Dooley, Damion, Duncan, William, Fey, Petra, Gaudet, Pascale, Harris, Nomi L, Joachimiak, Marcin, Kiani, Leila, Lubiana, Tiago, Munoz-Torres, Monica C, O'Neil, Shawn, Osumi-Sutherland, David, Puig, Aleix, Reese, Justin P, Reiser, Leonore, Robb, Sofia, Ruemping, Troy, Seager, James, Sid, Eric, Stefancsik, Ray, Weber, Magalie, Wood, Valerie, Haendel, Melissa A, and Mungall, Christopher J

Subjects
Computer Science - Artificial Intelligence
Abstract

Background: Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources. Results: We assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues. Conclusions: These findings suggest DRAGON-AI's potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

Published
2023
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5. Guidelines for reporting cell types: the MIRACL standard

Author

Lubiana, Tiago, Roncaglia, Paola, Mungall, Christopher J., Quardokus, Ellen M., Fortriede, Joshua D., Osumi-Sutherland, David, and Diehl, Alexander D.

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

Cell types are at the root of modern biology, and describing them is a core task of the Human Cell Atlas project. Surprisingly, there are no standards for reporting new cell types, leading to a gap between classes mentioned in biomedical literature and the Cell Ontology, the primary registry of cell types. Here we introduce the Minimal Information Reporting About a CelL (MIRACL) standard, a guideline for describing cell types alongside scientific articles. In a MIRACL sheet, authors organize a label, a diagnostic description, a taxon, an anatomical structure, and a parent cell class for each cell type of interest. The MIRACL standard bridges the gap between wet-lab researchers and ontologists, facilitating the integration of biomedical knowledge into ontologies and artificial intelligence systems., Comment: 8 pages, 1 figure, 1 table

Published
2022

7. OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies

Author

Jackson, Rebecca, Matentzoglu, Nicolas, Overton, James A, Vita, Randi, Balhoff, James P, Buttigieg, Pier Luigi, Carbon, Seth, Courtot, Melanie, Diehl, Alexander D, Dooley, Damion M, Duncan, William D, Harris, Nomi L, Haendel, Melissa A, Lewis, Suzanna E, Natale, Darren A, Osumi-Sutherland, David, Ruttenberg, Alan, Schriml, Lynn M, Smith, Barry, Stoeckert, Christian J, Vasilevsky, Nicole A, Walls, Ramona L, Zheng, Jie, Mungall, Christopher J, and Peters, Bjoern

Subjects
Information and Computing Sciences, Biological Sciences, Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Data Science, Biological Ontologies, Databases, Factual, Metadata, Data Format, Library and Information Studies, Bioinformatics and computational biology, Data management and data science
Abstract

Biological ontologies are used to organize, curate and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies (OBO) Foundry was created to address this by facilitating the development, harmonization, application and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here, we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology's compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable, federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data Findable, Accessible, Interoperable, and Reusable (FAIR). Database URL http://obofoundry.org/.

Published
2021

8. OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies

Author

Jackson, Rebecca C, Matentzoglu, Nicolas, Overton, James A, Vita, Randi, Balhoff, James P, Buttigieg, Pier Luigi, Carbon, Seth, Courtot, Melanie, Diehl, Alexander D, Dooley, Damion, Duncan, William, Harris, Nomi L, Haendel, Melissa A, Lewis, Suzanna E, Natale, Darren A, Osumi-Sutherland, David, Ruttenberg, Alan, Schriml, Lynn M, Smith, Barry, Stoeckert, Christian J, Vasilevsky, Nicole A, Walls, Ramona L, Zheng, Jie, Mungall, Christopher J, and Peters, Bjoern

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Philosophy and Religious Studies, Networking and Information Technology R&D (NITRD)
Abstract

Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies (OBO) Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data FAIR.

Published
2021

9. Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project

Author

Ong, Edison, Wang, Lucy L, Schaub, Jennifer, O’Toole, John F, Steck, Becky, Rosenberg, Avi Z, Dowd, Frederick, Hansen, Jens, Barisoni, Laura, Jain, Sanjay, de Boer, Ian H, Valerius, M Todd, Waikar, Sushrut S, Park, Christopher, Crawford, Dana C, Alexandrov, Theodore, Anderton, Christopher R, Stoeckert, Christian, Weng, Chunhua, Diehl, Alexander D, Mungall, Christopher J, Haendel, Melissa, Robinson, Peter N, Himmelfarb, Jonathan, Iyengar, Ravi, Kretzler, Matthias, Mooney, Sean, and He, Yongqun

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Kidney Disease, Networking and Information Technology R&D (NITRD), Generic health relevance, Renal and urogenital, Good Health and Well Being, Atlases as Topic, Big Data, Biological Ontologies, Humans, Kidney Diseases, Phenotype, Precision Medicine, Kidney Precision Medicine Project, Urology & Nephrology, Clinical sciences
Abstract

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

Published
2020

12. Cell type discovery using single-cell transcriptomics: implications for ontological representation

Author

Aevermann, Brian D, Novotny, Mark, Bakken, Trygve, Miller, Jeremy A, Diehl, Alexander D, Osumi-Sutherland, David, Lasken, Roger S, Lein, Ed S, and Scheuermann, Richard H

Subjects
Genetics, Networking and Information Technology R&D (NITRD), Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Big Data, Cell Lineage, Gene Expression Profiling, Humans, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Cells are fundamental function units of multicellular organisms, with different cell types playing distinct physiological roles in the body. The recent advent of single-cell transcriptional profiling using RNA sequencing is producing 'big data', enabling the identification of novel human cell types at an unprecedented rate. In this review, we summarize recent work characterizing cell types in the human central nervous and immune systems using single-cell and single-nuclei RNA sequencing, and discuss the implications that these discoveries are having on the representation of cell types in the reference Cell Ontology (CL). We propose a method, based on random forest machine learning, for identifying sets of necessary and sufficient marker genes, which can be used to assemble consistent and reproducible cell type definitions for incorporation into the CL. The representation of defined cell type classes and their relationships in the CL using this strategy will make the cell type classes being identified by high-throughput/high-content technologies findable, accessible, interoperable and reusable (FAIR), allowing the CL to serve as a reference knowledgebase of information about the role that distinct cellular phenotypes play in human health and disease.

Published
2018

16. Hydrothermal vents supporting persistent plumes and microbial chemoautotrophy at Gakkel Ridge (Arctic Ocean).

Author

Wegener, Gunter, Molari, Massimiliano, Purser, Autun, Diehl, Alexander, Albers, Elmar, Walter, Maren, Mertens, Christian, German, Christopher R., and Boetius, Antje

Subjects
HYDROTHERMAL vents, HYDROGEN oxidation, CARBON fixation, HYDROGEN as fuel, METAL sulfides
Abstract

Hydrothermal vents emit hot fluids enriched in energy sources for microbial life. Here, we compare the ecological and biogeochemical effects of hydrothermal venting of two recently discovered volcanic seamounts, Polaris and Aurora of the Gakkel Ridge, in the ice-covered Central Arctic Ocean. At both sites, persistent hydrothermal plumes increased up to 800  m into the deep Arctic Ocean. In the two non-buoyant plumes, rates of microbial carbon fixation were strongly elevated compared to background values of 0.5–1  μmol  m−3 day−1 in the Arctic deep water, which suggests increased chemoautotrophy on vent-derived energy sources. In the Polaris plume, free sulfide and up to 360  nM hydrogen enabled microorganisms to fix up to 46  μmol inorganic carbon (IC) m−3 day−1 . This energy pulse resulted in a strong increase in the relative abundance of SUP05 by 25% and Candidatus Sulfurimonas pluma by 7% of all bacteria. At Aurora, microorganisms fixed up to 35  μmol IC m−3 day−1 . Here, metal sulfides limited the bioavailability of reduced sulfur species, and the putative hydrogen oxidizer Ca. S. pluma constituted 35% and SUP05 10% of all bacteria. In accordance with this data, transcriptomic analysis showed a high enrichment of hydrogenase-coding transcripts in Aurora and an enrichment of transcripts coding for sulfur oxidation in Polaris. There was neither evidence for methane consumption nor a substantial increase in the abundance of putative methanotrophs or their transcripts in either plume. Together, our results demonstrate the dominance of hydrogen and sulfide as energy sources in Arctic hydrothermal vent plumes. [ABSTRACT FROM AUTHOR]

Published
2024
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17. The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability

Author

Diehl, Alexander D, Meehan, Terrence F, Bradford, Yvonne M, Brush, Matthew H, Dahdul, Wasila M, Dougall, David S, He, Yongqun, Osumi-Sutherland, David, Ruttenberg, Alan, Sarntivijai, Sirarat, Van Slyke, Ceri E, Vasilevsky, Nicole A, Haendel, Melissa A, Blake, Judith A, and Mungall, Christopher J

Subjects
Information and Computing Sciences, Artificial Intelligence, Networking and Information Technology R&D (NITRD), Human Genome, Genetics, Biological Ontologies, Cells, Natural Language Processing, Nervous System, Other Biological Sciences, Artificial Intelligence and Image Processing, Information Systems, Information and computing sciences
Abstract

BackgroundThe Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies.Construction and contentRecent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning.Utility and discussionThe CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs.ConclusionsThe ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community.

Published
2016

23. The Gene Ontology knowledgebase in 2023

Author

Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Huaiyu, Mi, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Kan Yan Chloe, Li, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin C C, Renzhi, Su, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Li, Ni, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley J F, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D’Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, Berardini, Tanya Z, Reiser, Leonore, Auchincloss, Andrea, Argoud-Puy, Ghislaine, Blatter, Marie-Claude, Boutet, Emmanuel, Breuza, Lionel, Casals-Casas, Cristina, Coudert, Elisabeth, Estreicher, Anne, Famiglietti, Maria Livia, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hulo, Chantal, Jungo, Florence, Le Mercier, Philippe, Lieberherr, Damien, Masson, Patrick, Pedruzzi, Ivo, Pourcel, Lucille, Poux, Sylvain, Rivoire, Catherine, Sundaram, Shyamala, Bateman, Alex, Bowler-Barnett, Emily, Bye-A-Jee, Hema, Denny, Paul, Ignatchenko, Alexandr, Ishtiaq, Rizwan, Lock, Antonia, Lussi, Yvonne, Magrane, Michele, Martin, Maria J, Orchard, Sandra, Raposo, Pedro, Speretta, Elena, Tyagi, Nidhi, Warner, Kate, Zaru, Rossana, Diehl, Alexander D, Chan, Juancarlos, Diamantakis, Stavros, Raciti, Daniela, Zarowiecki, Magdalena, Fisher, Malcolm, James-Zorn, Christina, Ponferrada, Virgilio, Zorn, Aaron, Ramachandran, Sridhar, Ruzicka, Leyla, and Westerfield, Monte

Subjects
gene annotation, gene function, knowledge graphs, Genetics, gene ontology, Molecular Biology, knowledgebase
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO—a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations—evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)—mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023

28. Enhanced olivine weathering in permeable sandy sediments from the North Sea – a laboratory study using flow-through reactors

Author

Köster, Male, Diehl, Alexander, Bach, Wolfgang, Kasten, Sabine, Köster, Male, Diehl, Alexander, Bach, Wolfgang, and Kasten, Sabine

Abstract

The Earth’s climate is increasingly warming due to ongoing anthropogenic carbon dioxide (CO2) emissions. In order to mitigate the human-made climate change and to meet the Paris Agreement goals of limiting the warming below 2°C, active carbon dioxide removal (CDR) from the atmosphere is of great importance in addition to massive CO2 emission reductions. A possible CDR method is rock weathering and the associated dissolution of minerals in the ocean, which leads to marine alkalinity enhancement and, thus, an enhanced flux of CO2 from the atmosphere into the ocean. In the framework of the project RETAKE, a consortium of the German Marine Research Alliance (DAM) research mission CDRmare, we investigate the potential, feasibility and side effects of olivine dissolution in high-energy coastal environments where strong currents and advection of seawater through permeable sediments have been proposed to accelerate weathering of silicate rocks. Here, we present data from laboratory experiments with flow-through reactors that are filled with permeable sandy sediments from the North Sea amended with different amounts and grain sizes of olivine. Permeable sediments are generally characterized by advective pore-water flow. Under advective conditions, higher weathering rates than those found in diffusion-controlled depositional settings are expected since the reaction products are rapidly removed and the formation of authigenic mineral coatings on olivine grains is prevented. The flow-through experiments are conducted under oxic conditions whereby air-saturated natural seawater is continuously pumped through the reactors. In addition to the permanent measurement of oxygen, pH and temperature, the circulating water is regularly sampled and alkalinity, dissolved inorganic carbon, major cation and trace metal (e.g., nickel) concentrations are analyzed. Preliminary results indicate an increase in alkalinity up to 3.2 mM in the reactor with the largest amount of olivine while the alk

Published
2023

29. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells

Author

FANTOM Consortium, Arner, Erik, Daub, Carsten O., Vitting-Seerup, Kristoffer, Andersson, Robin, Lilje, Berit, Drabløs, Finn, Lennartsson, Andreas, Rönnerblad, Michelle, Hrydziuszko, Olga, Vitezic, Morana, Freeman, Tom C., Alhendi, Ahmad M. N., Arner, Peter, Axton, Richard, Baillie, J. Kenneth, Beckhouse, Anthony, Bodega, Beatrice, Briggs, James, Brombacher, Frank, Davis, Margaret, Detmar, Michael, Ehrlund, Anna, Endoh, Mitsuhiro, Eslami, Afsaneh, Fagiolini, Michela, Fairbairn, Lynsey, Faulkner, Geoffrey J., Ferrai, Carmelo, Fisher, Malcolm E., Forrester, Lesley, Goldowitz, Daniel, Guler, Reto, Ha, Thomas, Hara, Mitsuko, Herlyn, Meenhard, Ikawa, Tomokatsu, Kai, Chieko, Kawamoto, Hiroshi, Khachigian, Levon M., Klinken, S. Peter, Kojima, Soichi, Koseki, Haruhiko, Klein, Sarah, Mejhert, Niklas, Miyaguchi, Ken, Mizuno, Yosuke, Morimoto, Mitsuru, Morris, Kelly J., Mummery, Christine, Nakachi, Yutaka, Ogishima, Soichi, Okada-Hatakeyama, Mariko, Okazaki, Yasushi, Orlando, Valerio, Ovchinnikov, Dmitry, Passier, Robert, Patrikakis, Margaret, Pombo, Ana, Qin, Xian-Yang, Roy, Sugata, Sato, Hiroki, Savvi, Suzana, Saxena, Alka, Schwegmann, Anita, Sugiyama, Daisuke, Swoboda, Rolf, Tanaka, Hiroshi, Tomoiu, Andru, Winteringham, Louise N., Wolvetang, Ernst, Yanagi-Mizuochi, Chiyo, Yoneda, Misako, Zabierowski, Susan, Zhang, Peter, Abugessaisa, Imad, Bertin, Nicolas, Diehl, Alexander D., Fukuda, Shiro, Furuno, Masaaki, Harshbarger, Jayson, Hasegawa, Akira, Hori, Fumi, Ishikawa-Kato, Sachi, Ishizu, Yuri, Itoh, Masayoshi, Kawashima, Tsugumi, Kojima, Miki, Kondo, Naoto, Lizio, Marina, Meehan, Terrence F., Mungall, Christopher J., Murata, Mitsuyoshi, Nishiyori-Sueki, Hiromi, Sahin, Serkan, Nagao-Sato, Sayaka, Severin, Jessica, de Hoon, Michiel J. L., Kawai, Jun, Kasukawa, Takeya, Lassmann, Timo, Suzuki, Harukazu, Kawaji, Hideya, Summers, Kim M., Wells, Christine, Hume, David A., Forrest, Alistair R. R., Sandelin, Albin, Carninci, Piero, and Hayashizaki, Yoshihide

Published
2015

30. The Gene Ontology knowledgebase in 2023

Author

Consortium, Gene Ontology, Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, Dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D'Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, Berardini, Tanya Z, Reiser, Leonore, Auchincloss, Andrea, Argoud-Puy, Ghislaine, Blatter, Marie-Claude, Boutet, Emmanuel, Breuza, Lionel, Casals-Casas, Cristina, Coudert, Elisabeth, Estreicher, Anne, Famiglietti, Maria Livia, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hulo, Chantal, Jungo, Florence, Le Mercier, Philippe, Lieberherr, Damien, Masson, Patrick, Pedruzzi, Ivo, Pourcel, Lucille, Poux, Sylvain, Rivoire, Catherine, Sundaram, Shyamala, Bateman, Alex, Bowler-Barnett, Emily, Bye-A-Jee, Hema, Denny, Paul, Ignatchenko, Alexandr, Ishtiaq, Rizwan, Lock, Antonia, Lussi, Yvonne, Magrane, Michele, Martin, Maria J, Orchard, Sandra, Raposo, Pedro, Speretta, Elena, Tyagi, Nidhi, Warner, Kate, Zaru, Rossana, Diehl, Alexander D, Chan, Juancarlos, Diamantakis, Stavros, Raciti, Daniela, Zarowiecki, Magdalena, Fisher, Malcolm, James-Zorn, Christina, Ponferrada, Virgilio, Zorn, Aaron, Ramachandran, Sridhar, Ruzicka, Leyla, and Westerfield, Monte

Subjects
Ecology,Evolution & Ethology, Cell Cycle & Chromosomes, Cell Biology
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023
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36. Volcanically hosted venting with indications of ultramafic influence at Aurora hydrothermal field on Gakkel Ridge

Author

German, Christopher R, Reeves, Eoghan P, Türke, Andreas, Diehl, Alexander, Albers, Elmar, Bach, Wolfgang, Purser, Autun, Ramalho, Sofia P, Suman, Stefano, Mertens, Christian, Walter, Maren, Ramirez-Llodra, Eva, Schlindwein, Vera, Bünz, Stefan, Boetius, Antje, German, Christopher R, Reeves, Eoghan P, Türke, Andreas, Diehl, Alexander, Albers, Elmar, Bach, Wolfgang, Purser, Autun, Ramalho, Sofia P, Suman, Stefano, Mertens, Christian, Walter, Maren, Ramirez-Llodra, Eva, Schlindwein, Vera, Bünz, Stefan, and Boetius, Antje

Abstract

The Aurora hydrothermal system, Arctic Ocean, hosts active submarine venting within an extensive field of relict mineral deposits. Here we show the site is associated with a neovolcanic mound located within the Gakkel Ridge rift-valley floor, but deep-tow camera and sidescan surveys reveal the site to be ≥100 m across—unusually large for a volcanically hosted vent on a slow-spreading ridge and more comparable to tectonically hosted systems that require large time-integrated heat-fluxes to form. The hydrothermal plume emanating from Aurora exhibits much higher dissolved CH4/Mn values than typical basalt-hosted hydrothermal systems and, instead, closely resembles those of high-temperature ultramafic-influenced vents at slow-spreading ridges. We hypothesize that deep-penetrating fluid circulation may have sustained the prolonged venting evident at the Aurora hydrothermal field with a hydrothermal convection cell that can access ultramafic lithologies underlying anomalously thin ocean crust at this ultraslow spreading ridge setting. Our findings have implications for ultra-slow ridge cooling, global marine mineral distributions, and the diversity of geologic settings that can host abiotic organic synthesis - pertinent to the search for life beyond Earth.

Published
2022

37. Hematopoietic cell types: Prototype for a revised cell ontology

Author

Diehl, Alexander D., Augustine, Alison Deckhut, Blake, Judith A., Cowell, Lindsay G., Gold, Elizabeth S., Gondré-Lewis, Timothy A., Masci, Anna Maria, Meehan, Terrence F., Morel, Penelope A., Nijnik, Anastasia, Peters, Bjoern, Pulendran, Bali, Scheuermann, Richard H., Yao, Q. Alison, Zand, Martin S., and Mungall, Christopher J.

Published
2011
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39. Positionspapier der Arbeitsgruppe 'Künstliche Intelligenz'

Author

Bienzeisler, Bernd, Brodbeck, Anja Carolina, Brumme, Hendrik, Bürkle, Heinz-Peter, Diehl, Alexander, Eichele, Karl, Engel, Klaus, Fleischmann, Stephanie, Frey, Timo, Graf, Nicole, Hanisch, Oliver, Hartmann, Jürgen, Joos, Daniel, Köhler, Daniel, Kraus, Carsten, Mandel, Klaus, Mayer, Florian, Pany, Bettina, Mühlbach, Björn-Helge, Schmidt, Peter, Rank, Ramon, Klömel, Bernhard, Schumm, Andreas, Schweiker, Peter, and Steinbrenner, Ralf

Published
2022
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40. Trace Element and Isotope Systematics in Vent Fluids and Sulphides From Maka Volcano, North Eastern Lau Spreading Centre: Insights Into Three-Component Fluid Mixing

Author

Klose, Lukas, primary, Keith, Manuel, additional, Hafermaas, Daniel, additional, Kleint, Charlotte, additional, Bach, Wolfgang, additional, Diehl, Alexander, additional, Wilckens, Frederike, additional, Peters, Christian, additional, Strauss, Harald, additional, Klemd, Reiner, additional, van Geldern, Robert, additional, Haase, Karsten Matthias, additional, and Koschinsky, Andrea, additional

Published
2021
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41. GENE REGULATION: Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells

Author

Arner, Erik, Daub, Carsten O., Vitting-Seerup, Kristoffer, Andersson, Robin, Lilje, Berit, Drabløs, Finn, Lennartsson, Andreas, Rönnerblad, Michelle, Hrydziuszko, Olga, Vitezic, Morana, Freeman, Tom C., Alhendi, Ahmad M. N., Arner, Peter, Axton, Richard, Baillie, Kenneth J., Beckhouse, Anthony, Bodega, Beatrice, Briggs, James, Brombacher, Frank, Davis, Margaret, Detmar, Michael, Ehrlund, Anna, Endoh, Mitsuhiro, Eslami, Afsaneh, Fagiolini, Michela, Fairbairn, Lynsey, Faulkner, Geoffrey J., Ferrai, Carmelo, Fisher, Malcolm E., Forrester, Lesley, Goldowitz, Daniel, Guler, Reto, Ha, Thomas, Hara, Mitsuko, Herlyn, Meenhard, Ikawa, Tomokatsu, Kai, Chieko, Kawamoto, Hiroshi, Khachigian, Levon M., Klinken, Peter S., Kojima, Soichi, Koseki, Haruhiko, Klein, Sarah, Mejhert, Niklas, Miyaguchi, Ken, Mizuno, Yosuke, Morimoto, Mitsuru, Morris, Kelly J., Mummery, Christine, Nakachi, Yutaka, Ogishima, Soichi, Okada-Hatakeyama, Mariko, Okazaki, Yasushi, Orlando, Valerio, Ovchinnikov, Dmitry, Passier, Robert, Patrikakis, Margaret, Pombo, Ana, Qin, Xian-Yang, Roy, Sugata, Sato, Hiroki, Savvi, Suzana, Saxena, Alka, Schwegmann, Anita, Sugiyama, Daisuke, Swoboda, Rolf, Tanaka, Hiroshi, Tomoiu, Andru, Winteringham, Louise N., Wolvetang, Ernst, Yanagi-Mizuochi, Chiyo, Yoneda, Misako, Zabierowski, Susan, Zhang, Peter, Abugessaisa, Imad, Bertin, Nicolas, Diehl, Alexander D., Fukuda, Shiro, Furuno, Masaaki, Harshbarger, Jayson, Hasegawa, Akira, Hori, Fumi, Ishikawa-Kato, Sachi, Ishizu, Yuri, Itoh, Masayoshi, Kawashima, Tsugumi, Kojima, Miki, Kondo, Naoto, Lizio, Marina, Meehan, Terrence F., Mungall, Christopher J., Murata, Mitsuyoshi, Nishiyori-Sueki, Hiromi, Sahin, Serkan, Nagao-Sato, Sayaka, Severin, Jessica, de Hoon, Michiel J. L., Kawai, Jun, Kasukawa, Takeya, Lassmann, Timo, Suzuki, Harukazu, Kawaji, Hideya, Summers, Kim M., Wells, Christine, Hume, David A., Forrest, Alistair R. R., Sandelin, Albin, Carninci, Piero, and Hayashizaki, Yoshihide

Published
2015
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44. Autorinnen und Autoren

Author

Adli, Mazda, primary, Bandelow, Borwin, additional, Barton, Barbara, additional, Batra, Anil, additional, Bauer, Michael, additional, Bechdolf, Andreas, additional, Becker, Thomas, additional, Berger, Mathias, additional, Berner, Michael M., additional, Bohus, Martin, additional, Briken, Peer, additional, Zwaan, Martina de, additional, Diehl, Alexander, additional, Eucker, Sabine, additional, Fiedler, Peter, additional, Fleischhacker, W. Wolfgang, additional, Frölich, Lutz, additional, Frommberger, Ulrich, additional, Gaebel, Wolfgang, additional, Gouzoulis-Mayfrank, Euphrosyne, additional, Hajak, Göran, additional, Hausner, Lucrezia, additional, Heinz, Andreas, additional, Henningsen, Peter, additional, Herpertz, Sabine C., additional, Herpertz, Stephan, additional, Herpertz-Dahlmann, Beate, additional, Hiemke, Christoph, additional, Hohagen, Fritz, additional, Jähne, Andreas, additional, Jessen, Frank, additional, Karamatskos, Evangelos, additional, Klingberg, Stefan, additional, Klosterkötter, Joachim, additional, Kösters, Markus, additional, Lambert, Martin, additional, Leucht, Stefan, additional, Lieb, Klaus, additional, Linden, Michael, additional, Maercker, Andreas, additional, Mann, Karl F., additional, Müller, Christian A., additional, Müller-Isberner, J. Rüdiger, additional, Naber, Dieter, additional, Nedopil, Norbert, additional, Neumayr, Christina, additional, Neuner, Irene, additional, Nieder, Timo O., additional, Uwe Petersen, Kay, additional, Philipsen, Alexandra, additional, Pollmächer, Thomas, additional, Priebe, Kathlen, additional, Remschmidt, Helmut, additional, Rief, Winfried, additional, Riemann, Dieter, additional, Rösler, Michael, additional, Rüther, Tobias, additional, Scherbaum, Norbert, additional, Schläpfer, Thomas, additional, Schmahl, Christian, additional, Schmauß, Max, additional, Schmidt-Kraepelin, Christian, additional, Schramm, Elisabeth, additional, Soyka, Michael, additional, Spiegelhalder, Kai, additional, Stieglitz, Rolf-Dieter, additional, Stiglmayr, Christian, additional, Theodor te Wildt, Bert, additional, Voderholzer, Ulrich, additional, von Hecker, Birgit, additional, Wetter, Thomas C., additional, Wolfersdorf, Manfred, additional, and Zipfel, Stephan, additional

Published
2015
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45. OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies

Author

Jackson, Rebecca, primary, Matentzoglu, Nicolas, additional, Overton, James A, additional, Vita, Randi, additional, Balhoff, James P, additional, Buttigieg, Pier Luigi, additional, Carbon, Seth, additional, Courtot, Melanie, additional, Diehl, Alexander D, additional, Dooley, Damion M, additional, Duncan, William D, additional, Harris, Nomi L, additional, Haendel, Melissa A, additional, Lewis, Suzanna E, additional, Natale, Darren A, additional, Osumi-Sutherland, David, additional, Ruttenberg, Alan, additional, Schriml, Lynn M, additional, Smith, Barry, additional, Stoeckert Jr., Christian J, additional, Vasilevsky, Nicole A, additional, Walls, Ramona L, additional, Zheng, Jie, additional, Mungall, Christopher J, additional, and Peters, Bjoern, additional

Published
2021
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48. A promoter-level mammalian expression atlas

Author

Forrest, Alistair R. R., Kawaji, Hideya, Rehli, Michael, Kenneth Baillie, J., de Hoon, Michiel J. L., Haberle, Vanja, Lassmann, Timo, Kulakovskiy, Ivan V., Lizio, Marina, Itoh, Masayoshi, Andersson, Robin, Mungall, Christopher J., Meehan, Terrence F., Schmeier, Sebastian, Bertin, Nicolas, Jørgensen, Mette, Dimont, Emmanuel, Arner, Erik, Schmidl, Christian, Schaefer, Ulf, Medvedeva, Yulia A., Plessy, Charles, Vitezic, Morana, Severin, Jessica, Semple, Colin A., Ishizu, Yuri, Young, Robert S., Francescatto, Margherita, Alam, Intikhab, Albanese, Davide, Altschuler, Gabriel M., Arakawa, Takahiro, Archer, John A. C., Arner, Peter, Babina, Magda, Rennie, Sarah, Balwierz, Piotr J., Beckhouse, Anthony G., Pradhan-Bhatt, Swati, Blake, Judith A., Blumenthal, Antje, Bodega, Beatrice, Bonetti, Alessandro, Briggs, James, Brombacher, Frank, Maxwell Burroughs, A., Califano, Andrea, Cannistraci, Carlo V., Carbajo, Daniel, Chen, Yun, Chierici, Marco, Ciani, Yari, Clevers, Hans C., Dalla, Emiliano, Davis, Carrie A., Detmar, Michael, Diehl, Alexander D., Dohi, Taeko, Drabløs, Finn, Edge, Albert S. B., Edinger, Matthias, Ekwall, Karl, Endoh, Mitsuhiro, Enomoto, Hideki, Fagiolini, Michela, Fairbairn, Lynsey, Fang, Hai, Farach-Carson, Mary C., Faulkner, Geoffrey J., Favorov, Alexander V., Fisher, Malcolm E., Frith, Martin C., Fujita, Rie, Fukuda, Shiro, Furlanello, Cesare, Furuno, Masaaki, Furusawa, Jun-ichi, Geijtenbeek, Teunis B., Gibson, Andrew P., Gingeras, Thomas, Goldowitz, Daniel, Gough, Julian, Guhl, Sven, Guler, Reto, Gustincich, Stefano, Ha, Thomas J., Hamaguchi, Masahide, Hara, Mitsuko, Harbers, Matthias, Harshbarger, Jayson, Hasegawa, Akira, Hasegawa, Yuki, Hashimoto, Takehiro, Herlyn, Meenhard, Hitchens, Kelly J., Ho Sui, Shannan J., Hofmann, Oliver M., Hoof, Ilka, Hori, Fumi, Huminiecki, Lukasz, Iida, Kei, Ikawa, Tomokatsu, Jankovic, Boris R., Jia, Hui, Joshi, Anagha, Jurman, Giuseppe, Kaczkowski, Bogumil, Kai, Chieko, Kaida, Kaoru, Kaiho, Ai, Kajiyama, Kazuhiro, Kanamori-Katayama, Mutsumi, Kasianov, Artem S., Kasukawa, Takeya, Katayama, Shintaro, Kato, Sachi, Kawaguchi, Shuji, Kawamoto, Hiroshi, Kawamura, Yuki I., Kawashima, Tsugumi, Kempfle, Judith S., Kenna, Tony J., Kere, Juha, Khachigian, Levon M., Kitamura, Toshio, Peter Klinken, S., Knox, Alan J., Kojima, Miki, Kojima, Soichi, Kondo, Naoto, Koseki, Haruhiko, Koyasu, Shigeo, Krampitz, Sarah, Kubosaki, Atsutaka, Kwon, Andrew T., Laros, Jeroen F. J., Lee, Weonju, Lennartsson, Andreas, Li, Kang, Lilje, Berit, Lipovich, Leonard, Mackay-sim, Alan, Manabe, Ri-ichiroh, Mar, Jessica C., Marchand, Benoit, Mathelier, Anthony, Mejhert, Niklas, Meynert, Alison, Mizuno, Yosuke, de Lima Morais, David A., Morikawa, Hiromasa, Morimoto, Mitsuru, Moro, Kazuyo, Motakis, Efthymios, Motohashi, Hozumi, Mummery, Christine L., Murata, Mitsuyoshi, Nagao-Sato, Sayaka, Nakachi, Yutaka, Nakahara, Fumio, Nakamura, Toshiyuki, Nakamura, Yukio, Nakazato, Kenichi, van Nimwegen, Erik, Ninomiya, Noriko, Nishiyori, Hiromi, Noma, Shohei, Nozaki, Tadasuke, Ogishima, Soichi, Ohkura, Naganari, Ohmiya, Hiroko, Ohno, Hiroshi, Ohshima, Mitsuhiro, Okada-Hatakeyama, Mariko, Okazaki, Yasushi, Orlando, Valerio, Ovchinnikov, Dmitry A., Pain, Arnab, Passier, Robert, Patrikakis, Margaret, Persson, Helena, Piazza, Silvano, Prendergast, James G. D., Rackham, Owen J. L., Ramilowski, Jordan A., Rashid, Mamoon, Ravasi, Timothy, Rizzu, Patrizia, Roncador, Marco, Roy, Sugata, Rye, Morten B., Saijyo, Eri, Sajantila, Antti, Saka, Akiko, Sakaguchi, Shimon, Sakai, Mizuho, Sato, Hiroki, Satoh, Hironori, Savvi, Suzana, Saxena, Alka, Schneider, Claudio, Schultes, Erik A., Schulze-Tanzil, Gundula G., Schwegmann, Anita, Sengstag, Thierry, Sheng, Guojun, Shimoji, Hisashi, Shimoni, Yishai, Shin, Jay W., Simon, Christophe, Sugiyama, Daisuke, Sugiyama, Takaaki, Suzuki, Masanori, Suzuki, Naoko, Swoboda, Rolf K., ’t Hoen, Peter A. C., Tagami, Michihira, Takahashi, Naoko, Takai, Jun, Tanaka, Hiroshi, Tatsukawa, Hideki, Tatum, Zuotian, Thompson, Mark, Toyoda, Hiroo, Toyoda, Tetsuro, Valen, Eivind, van de Wetering, Marc, van den Berg, Linda M., Verardo, Roberto, Vijayan, Dipti, Vorontsov, Ilya E., Wasserman, Wyeth W., Watanabe, Shoko, Wells, Christine A., Winteringham, Louise N., Wolvetang, Ernst, Wood, Emily J., Yamaguchi, Yoko, Yamamoto, Masayuki, Yoneda, Misako, Yonekura, Yohei, Yoshida, Shigehiro, Zabierowski, Susan E., Zhang, Peter G., Zhao, Xiaobei, Zucchelli, Silvia, Summers, Kim M., Suzuki, Harukazu, Daub, Carsten O., Kawai, Jun, Heutink, Peter, Hide, Winston, Freeman, Tom C., Lenhard, Boris, Bajic, Vladimir B., Taylor, Martin S., Makeev, Vsevolod J., Sandelin, Albin, Hume, David A., Carninci, Piero, and Hayashizaki, Yoshihide

Published
2014
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49. Compositions of hydrothermal vent fluids as a guide to subseafloor mineralization processes

Author

Bach , Wolfgang and Diehl , Alexander

Abstract

Studying active hydrothermal systems in the deep-sea provides unique opportunities for furthering our understanding of how polymetallic seafloor massive sulfide accumulations form. The possibility of sampling the ore-forming fluids that are emitted through sulfide-sulfate chimneys is particularly powerful. The use of gas-tight samplers in collecting hydrothermal vent fluids facilitates measurements of the contents of dissolved gases and metals and allows for accurate reconstructions of in situ pH and redox conditions. Metal transport in seafloor hydrothermal systems is affected by fluid-rock interactions, magma degassing, phase separation, and subseafloor mixing of the upwelling hydrothermal fluids with entrained seawater. The composition of basement hosting deep-sea hydrothermal vent systems, i.e. the type of rock involved in fluid-rock interactions, ranges from ultramafic to felsic. Geotectonic settings of vent systems vary from mid-ocean ridges to backarc spreading centers to island arc and intraplate volcanoes, which show strong contrasts in water depths and influx of magmatic fluids. Our recent compilation of vent fluid data (doi:10.1029/2020GC009385) allows a first complete assessment of how these differences affect the compositions of fluids in the root zones of hydrothermal systems. Beyond an examination of these general differences, valuable insights into processes in the discharge zone of hydrothermal systems can be obtained from detailed fluid sampling in individual vent fields. We present examples from selected arc/backarc hydrothermal vent sites in felsic crust for how vent fluid compositional data and thermodynamic computations can yield detailed insights into km-scale metal transport as well as smaller scale processes of zone refining.

Published
2021
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50. Three-component fluid mixing: Evidence from trace element and isotope systematics in vent fluids and sulphides from Maka volcano, North Eastern Lau Spreading Centre

Author

Klose, Lukas, Keith, Manuel, Hafermaas, Daniel, Kleint, Charlotte, Bach, Wolfgang, Diehl, Alexander, Wilckens, Frederike, Peters, Christian, Strauss, Harald, Klemd, Reiner, Haase, Karsten, and Koschinsky, Andrea

Abstract

The axial volcanic edifice of Maka at the North Eastern Lau Spreading Centre shows intense hydrothermal activity at two vent sites (Maka HF and Maka South) emitting fluids of distinct composition. We present trace element and isotope data for hydrothermal fluids and related sulphide precipitates that actively form on the seafloor at 1525 to 1543 m water depth. Hydrothermal activity at Maka HF is present as vigorously venting black smoker-type fluids reaching temperatures of ~330��C. High metal (e.g. Fe, Mn, Li) and REE contents in the vent fluids, are indicative for a rock-buffered hydrothermal system at low water/rock ratios. At Maka South venting of white smoke at up to 300��C occurs at several sites. Measured fluid pH (4.53-5.42) and Mg, SO4 and Cl concentrations are depleted compared to seawater, whereas Li, Mn and H2S are enriched, indicating a three-component mixing model between seawater, a boiling-induced low Cl vapor and a black smoker-type fluid at Maka South. Trace element systematics in hydrothermal pyrite also report on the contribution of these different fluid-types. Pyrite that precipitates from low Cl vapor-rich fluids at Maka South is characterized by high As/Co (>10) and Sb/Pb (>0.1) values that we relate to a boiling-induced element fractionation between the vapor (As, Sb) and liquid phase (Co, Pb). The Se/Ge ratio in pyrite may be used as a new tracer for fluid-seawater mixing. Sulfur and Pb isotopes in hydrothermal sulphides indicate a common metal(loid) source at the two vent sites by host rock leaching in the reaction zone.

Published
2021
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