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Renn D, Shepard L, Vancea A, Karan R, Arold ST, Rueping M. Novel Enzymes From the Red Sea Brine Pools: Current State and Potential. Front Microbiol 2021; 12:732856. [PMID: 34777282 PMCID: PMC8578733 DOI: 10.3389/fmicb.2021.732856] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/05/2021] [Indexed: 11/23/2022] Open
Abstract
The Red Sea is a marine environment with unique chemical characteristics and physical topographies. Among the various habitats offered by the Red Sea, the deep-sea brine pools are the most extreme in terms of salinity, temperature and metal contents. Nonetheless, the brine pools host rich polyextremophilic bacterial and archaeal communities. These microbial communities are promising sources for various classes of enzymes adapted to harsh environments - extremozymes. Extremozymes are emerging as novel biocatalysts for biotechnological applications due to their ability to perform catalytic reactions under harsh biophysical conditions, such as those used in many industrial processes. In this review, we provide an overview of the extremozymes from different Red Sea brine pools and discuss the overall biotechnological potential of the Red Sea proteome.
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Affiliation(s)
- Dominik Renn
- KAUST Catalysis Center (KCC), Division of Physical Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Institute of Organic Chemistry, RWTH Aachen, Aachen, Germany
| | - Lera Shepard
- KAUST Catalysis Center (KCC), Division of Physical Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Alexandra Vancea
- Computational Bioscience Research Center (CBRC), Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Ram Karan
- KAUST Catalysis Center (KCC), Division of Physical Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Stefan T. Arold
- Computational Bioscience Research Center (CBRC), Division of Biological and Environmental Science and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Centre de Biologie Structurale, CNRS, INSERM, Université de Montpellier, Montpellier, France
| | - Magnus Rueping
- KAUST Catalysis Center (KCC), Division of Physical Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Institute for Experimental Molecular Imaging (ExMI), University Clinic, RWTH Aachen, Aachen, Germany
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Alam I, Antunes A, Kamau AA, Ba Alawi W, Kalkatawi M, Stingl U, Bajic VB. INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles. PLoS One 2013; 8:e82210. [PMID: 24324765 PMCID: PMC3855842 DOI: 10.1371/journal.pone.0082210] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2013] [Accepted: 10/22/2013] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. RESULTS We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. CONCLUSIONS We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo.
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Affiliation(s)
- Intikhab Alam
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
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Wruck W, Peuker M, Regenbrecht CRA. Data management strategies for multinational large-scale systems biology projects. Brief Bioinform 2012; 15:65-78. [PMID: 23047157 PMCID: PMC3896927 DOI: 10.1093/bib/bbs064] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don’t Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects.
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Affiliation(s)
- Wasco Wruck
- Institute of Pathology, Charite - Universitaetsmedizin Berlin, Chariteplatz 1, 10117 Berlin. Tel.: +49 30 2093 8951; Fax: +49 30 450 536 909;
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Chen YA, Tripathi LP, Mizuguchi K. TargetMine, an integrated data warehouse for candidate gene prioritisation and target discovery. PLoS One 2011; 6:e17844. [PMID: 21408081 PMCID: PMC3050930 DOI: 10.1371/journal.pone.0017844] [Citation(s) in RCA: 86] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2010] [Accepted: 02/14/2011] [Indexed: 11/19/2022] Open
Abstract
Prioritising candidate genes for further experimental characterisation is a
non-trivial challenge in drug discovery and biomedical research in general. An
integrated approach that combines results from multiple data types is best
suited for optimal target selection. We developed TargetMine, a data warehouse
for efficient target prioritisation. TargetMine utilises the InterMine
framework, with new data models such as protein-DNA interactions integrated in a
novel way. It enables complicated searches that are difficult to perform with
existing tools and it also offers integration of custom annotations and in-house
experimental data. We proposed an objective protocol for target prioritisation
using TargetMine and set up a benchmarking procedure to evaluate its
performance. The results show that the protocol can identify known
disease-associated genes with high precision and coverage. A demonstration
version of TargetMine is available at http://targetmine.nibio.go.jp/.
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Affiliation(s)
- Yi-An Chen
- National Institute of Biomedical Innovation,
Saito-Asagi, Ibaraki, Osaka, Japan
- Graduated School of Frontier Biosciences,
Osaka University, Yamadaoka, Suita, Osaka, Japan
| | - Lokesh P. Tripathi
- National Institute of Biomedical Innovation,
Saito-Asagi, Ibaraki, Osaka, Japan
| | - Kenji Mizuguchi
- National Institute of Biomedical Innovation,
Saito-Asagi, Ibaraki, Osaka, Japan
- Graduated School of Frontier Biosciences,
Osaka University, Yamadaoka, Suita, Osaka, Japan
- * E-mail:
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ePlant and the 3D data display initiative: integrative systems biology on the world wide web. PLoS One 2011; 6:e15237. [PMID: 21249219 PMCID: PMC3018417 DOI: 10.1371/journal.pone.0015237] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2010] [Accepted: 11/01/2010] [Indexed: 12/22/2022] Open
Abstract
Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales. These computational tools are also typically limited by two-dimensional displays and programmatic implementations that require separate configurations for each of the user's computing devices and recompilation for functional expansion. Towards overcoming these limitations we have developed "ePlant" (http://bar.utoronto.ca/eplant) - a suite of open-source world wide web-based tools for the visualization of large-scale data sets from the model organism Arabidopsis thaliana. These tools display data spanning multiple biological scales on interactive three-dimensional models. Currently, ePlant consists of the following modules: a sequence conservation explorer that includes homology relationships and single nucleotide polymorphism data, a protein structure model explorer, a molecular interaction network explorer, a gene product subcellular localization explorer, and a gene expression pattern explorer. The ePlant's protein structure explorer module represents experimentally determined and theoretical structures covering >70% of the Arabidopsis proteome. The ePlant framework is accessed entirely through a web browser, and is therefore platform-independent. It can be applied to any model organism. To facilitate the development of three-dimensional displays of biological data on the world wide web we have established the "3D Data Display Initiative" (http://3ddi.org).
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O'Neill K, Garcia A, Schwegmann A, Jimenez RC, Jacobson D, Hermjakob H. OntoDas – a tool for facilitating the construction of complex queries to the Gene Ontology. BMC Bioinformatics 2008; 9:437. [PMID: 18925933 PMCID: PMC2579441 DOI: 10.1186/1471-2105-9-437] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2008] [Accepted: 10/16/2008] [Indexed: 11/17/2022] Open
Abstract
Background Ontologies such as the Gene Ontology can enable the construction of complex queries over biological information in a conceptual way, however existing systems to do this are too technical. Within the biological domain there is an increasing need for software that facilitates the flexible retrieval of information. OntoDas aims to fulfil this need by allowing the definition of queries by selecting valid ontology terms. Results OntoDas is a web-based tool that uses information visualisation techniques to provide an intuitive, interactive environment for constructing ontology-based queries against the Gene Ontology Database. Both a comprehensive use case and the interface itself were designed in a participatory manner by working with biologists to ensure that the interface matches the way biologists work. OntoDas was further tested with a separate group of biologists and refined based on their suggestions. Conclusion OntoDas provides a visual and intuitive means for constructing complex queries against the Gene Ontology. It was designed with the participation of biologists and compares favourably with similar tools. It is available at
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Castro AG, Rocca-Serra P, Stevens R, Taylor C, Nashar K, Ragan MA, Sansone SA. The use of concept maps during knowledge elicitation in ontology development processes--the nutrigenomics use case. BMC Bioinformatics 2006; 7:267. [PMID: 16725019 PMCID: PMC1524992 DOI: 10.1186/1471-2105-7-267] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2005] [Accepted: 05/25/2006] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Incorporation of ontologies into annotations has enabled 'semantic integration' of complex data, making explicit the knowledge within a certain field. One of the major bottlenecks in developing bio-ontologies is the lack of a unified methodology. Different methodologies have been proposed for different scenarios, but there is no agreed-upon standard methodology for building ontologies. The involvement of geographically distributed domain experts, the need for domain experts to lead the design process, the application of the ontologies and the life cycles of bio-ontologies are amongst the features not considered by previously proposed methodologies. RESULTS Here, we present a methodology for developing ontologies within the biological domain. We describe our scenario, competency questions, results and milestones for each methodological stage. We introduce the use of concept maps during knowledge acquisition phases as a feasible transition between domain expert and knowledge engineer. CONCLUSION The contributions of this paper are the thorough description of the steps we suggest when building an ontology, example use of concept maps, consideration of applicability to the development of lower-level ontologies and application to decentralised environments. We have found that within our scenario conceptual maps played an important role in the development process.
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Affiliation(s)
- Alexander Garcia Castro
- Microarray Informatics Team, The European Bioinformatics Institute – European Molecular Biology Laboratory Outstation, Wellcome Trust Genome Campus CB10 1SD, Cambridge Hinxton, UK
- Australian Research Council Centre in Bioinformatics, Institute for Molecular Bioscience, The University of Queensland 4072, St Lucia, Australia
- Institute for Molecular Bioscience, The University of Queensland 4072, Brisbane, Australia
- Australian Centre for Plant Functional Genomics, The University of Queensland 4072, Brisbane, Australia
| | - Philippe Rocca-Serra
- Microarray Informatics Team, The European Bioinformatics Institute – European Molecular Biology Laboratory Outstation, Wellcome Trust Genome Campus CB10 1SD, Cambridge Hinxton, UK
| | - Robert Stevens
- School of Computer Science, University of Manchester, Kilburn Building, Oxford Road Manchester M13 9PL, Manchester, UK
| | - Chris Taylor
- Microarray Informatics Team, The European Bioinformatics Institute – European Molecular Biology Laboratory Outstation, Wellcome Trust Genome Campus CB10 1SD, Cambridge Hinxton, UK
| | - Karim Nashar
- School of Computer Science, University of Manchester, Kilburn Building, Oxford Road Manchester M13 9PL, Manchester, UK
| | - Mark A Ragan
- Australian Research Council Centre in Bioinformatics, Institute for Molecular Bioscience, The University of Queensland 4072, St Lucia, Australia
- Institute for Molecular Bioscience, The University of Queensland 4072, Brisbane, Australia
| | - Susanna-Assunta Sansone
- Microarray Informatics Team, The European Bioinformatics Institute – European Molecular Biology Laboratory Outstation, Wellcome Trust Genome Campus CB10 1SD, Cambridge Hinxton, UK
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